For the past few years,the prevalence of cardiovascular disease has been showing a year-on-year increase,with a death rate of 2/5.Coronary heart disease(CHD)rates have increased 41%since 1990,which is the number one d...For the past few years,the prevalence of cardiovascular disease has been showing a year-on-year increase,with a death rate of 2/5.Coronary heart disease(CHD)rates have increased 41%since 1990,which is the number one disease endangering human health in the world today.The risk indicators of CHD are complicated,so selecting effective methods to screen the risk characteristics can make the risk predictionmore efficient.In this paper,we present a comprehensive analysis ofCHDrisk indicators fromboth data and algorithmic levels,propose a method for CHDrisk indicator identification based on multi-angle integrated measurements and Sequential Backward Selection(SBS),and then build a risk prediction model.In the multi-angle integrated measurements stage,mRMR(Maximum Relevance Minimum Redundancy)is selected from the angle of feature correlation and redundancy of the dataset itself,SHAPRF(SHapley Additive exPlanations-Random Forest)is selected from the angle of interpretation of each feature to the results,and ARFS-RF(Algorithmic Randomness Feature Selection Random Forest)is selected from the angle of statistical interpretation of classification algorithm to measure the degree of feature importance.In the SBS stage,the features with low scores are deleted successively,and the accuracy of LightGBM(Light Gradient Boosting Machine)model is used as the evaluation index to select the final feature subset.This new risk assessment method is used to identify important factors affecting CHD,and the CHD dataset from the Kaggle website is used as the study subject.Finally,11 features are retained to construct a risk assessment indicator system for CHD.Using the LightGBM classifier as the core evaluationmetric,ourmethod achieved an accuracy of 0.8656 on the Kaggle CHD dataset(4238 samples,16 initial features),outperforming individual feature selection methods(mRMR,SHAP-RF,ARFS-RF)in both accuracy and feature reduction.This demonstrates the novelty and effectiveness of our multi-angle integrated measurement approach combined with SBS in building a concise yet highly predictive CHD risk model.展开更多
The electric vertical takeoff and landing(e VTOL)aircraft shows great potential for rapid military personnel deployment on the battlefield.However,its susceptibility to control loss,complex crashes,and extremely limit...The electric vertical takeoff and landing(e VTOL)aircraft shows great potential for rapid military personnel deployment on the battlefield.However,its susceptibility to control loss,complex crashes,and extremely limited bottom energy-absorbing space demands higher comprehensive crashworthiness of its subfloor thin-walled structures.This study investigated the energy absorption capacity of novel concave polygonal carbon fiber reinforced plastics(CFRP)tubes under multi-angle collisions.Quasistatic compression experiments and finite element simulations were conducted to assess the failure mode and energy absorption.The influences of cross-section shapes,loading conditions,and geometry parameters on crashworthiness metrics were further analyzed.The results revealed that,under the similar weight,concave polygonal tubes exhibited superior energy absorption under axial loads compared to regular polygonal and circular tubes,attributed to the increased number of axial splits.However,both regular and concave polygonal tubes,particularly the latter,demonstrated reduced oblique energy absorption compared to traditional square tubes with the increasing ratio of SEA value decreased from 20%-16%.Notably,this reduction in energy absorption can be compensated for by the implementation of inward and outward crusher plugs,and with them,the concave polygonal tubes demonstrated outstanding overall crashworthiness performance under multiple loading conditions.This concave cross-sectional design methods could serve as a guidance for the development of the eVTOL subfloor.展开更多
During the image generation phase,the parserfree Flow-Style-VTON model(PF-Flow-Style-VTON),which utilizes distilled appearance flows,faces two main challenges:blurring,deformation,occlusion,or loss of the arm or palm ...During the image generation phase,the parserfree Flow-Style-VTON model(PF-Flow-Style-VTON),which utilizes distilled appearance flows,faces two main challenges:blurring,deformation,occlusion,or loss of the arm or palm regions in the generated image when these regions of the person occlude the garment;blurring and deformation in the generated image when the person performs large pose movements and the target garment is complex with detailed patterns.To solve these two problems,an improved virtual try-on network model,denoted as IPF-Flow-Style-VTON,is proposed.Firstly,a target warped garment mask refinement module(M-RM)is introduced to refine the warped garment mask and remove erroneous information in the arm and palm regions,thereby improving the quality of subsequent image generation.Secondly,an improved global attention module(GAM)is integrated into the original image generation network,enhancing the ResUNet’s understanding of global context and optimizing the fusion of local features and global information,thereby further improving image generation quality.Finally,the UniPose model is used to provide the pose keypoint information of the target person image,guiding the task execution during the image generation phase.Experiments conducted on the VITON dataset show that the proposed method outperforms the original method,Flow-Style-VTON,by 5.4%,0.3%,6.7%,and 2.2%in Frchet inception distance(FID),structural similarity index measure(SSIM),learned perceptual image patch similarity(LPIPS),and peak signal-to-noise ratio(PSNR),respectively.Overall,the proposed method effectively improves upon the shortcomings of the original network and achieves better visual results.展开更多
Plant phenomics has the potential to accelerate progress in understanding gene functions and environmental responses. Progress has been made in automating high-throughput plant phenotyping. However, few studies have i...Plant phenomics has the potential to accelerate progress in understanding gene functions and environmental responses. Progress has been made in automating high-throughput plant phenotyping. However, few studies have investigated automated rice panicle counting. This paper describes a novel method for automatically and nonintrusively determining rice panicle numbers during the full heading stage by analyzing color images of rice plants taken from multiple angles. Pot-grown rice plants were transferred via an industrial conveyer to an imaging chamber. Color images from different angles were automatically acquired as a turntable rotated the plant. The images were then analyzed and the panicle number of each plant was determined. The image analysis pipeline consisted of extracting the i2 plane from the original color image, segmenting the image, discriminating the panicles from the rest of the plant using an artificial neural network, and calculating the panicle number in the current image. The panicle number of the plant was taken as the maximum of the panicle numbers extracted from all 12 multi-angle images. A total of 105 rice plants during the full heading stage were examined to test the performance of the method. The mean absolute error of the manual and automatic count was 0.5, with 95.3% of the plants yielding absolute errors within ± 1. The method will be useful for evaluating rice panicles and will serve as an important supplementary method for high-throughput rice phenotyping.展开更多
The traditional remote sensing mainly detects the ground vertically to obtain the 2D information but it is hard to get adequate parameters for the quantitative remote sensing to invert land features. The multi-angle o...The traditional remote sensing mainly detects the ground vertically to obtain the 2D information but it is hard to get adequate parameters for the quantitative remote sensing to invert land features. The multi-angle observation can get more detailed and reliable 3D structural parameters of targets, so it makes the quantitative remote sensing applicable. During the process of reflecting, scattering and transmitting the electromagnetic wave, minerals and rocks could reveal the polarized features related to the nature of themselves. Therefore, it has become a new approach of quantitative remote sensing to detect multi-angle polarized information of minerals and rocks. In respect that the polarized reflectance always goes with the bidirectional one, we can obtain the 3D spatial distribution of targets by a polarized means together with detecting its bi-directional reflectance. From the perspective of multi-angle polarized remote sensing mechanism, the quantitative relationship between multi-angle polarized reflectance and the BRDF is studied in this paper. And it is testified that the bi-directional reflectance, polarized reflectance of 45° and the mean value of polarized reflectance are equal to that of the corresponding azimuth angle, zenith angle, detection angle and detection channels in 27t space by experiment.展开更多
Ground-based synthetic aperture radar(GB-SAR) has been successfully applied to the ground deformation monitoring.However, due to the short length of the GB-SAR platform, the scope of observation is largely limited. Th...Ground-based synthetic aperture radar(GB-SAR) has been successfully applied to the ground deformation monitoring.However, due to the short length of the GB-SAR platform, the scope of observation is largely limited. The practical applications drive us to make improvements on the conventional linear rail GB-SAR system in order to achieve larger field imaging. First, a turntable is utilized to support the rotational movement of the radar.Next, a series of high-squint scanning is performed with multiple squint angles. Further, the high squint modulation phase of the echo data is eliminated. Then, a new multi-angle imaging method is performed in the wave number domain to expand the field of view. Simulation and real experiments verify the effectiveness of this method.展开更多
Although important progresses have been already made in face detection,many false faces can be found in detection results and false detection rate is influenced by some factors,such as rotation and tilt of human face,...Although important progresses have been already made in face detection,many false faces can be found in detection results and false detection rate is influenced by some factors,such as rotation and tilt of human face,complicated background,illumination,scale,cloak and hairstyle.This paper proposes a new method called DP-Adaboost algorithm to detect multi-angle human face and improve the correct detection rate.An improved Adaboost algorithm with the fusion of frontal face classifier and a profile face classifier is used to detect the multi-angle face.An improved horizontal differential projection algorithm is put forward to remove those non-face images among the preliminary detection results from the improved Adaboost algorithm.Experiment results show that compared with the classical Adaboost algorithm with a frontal face classifier,the textual DP-Adaboost algorithm can reduce false rate significantly and improve hit rate in multi-angle face detection.展开更多
This study clarifies the seepage characteristics of complex fractured pressure-sensitive reservoirs,and addresses a common technological problem,that is the alteration of the permeability degree of the reservoir bed(k...This study clarifies the seepage characteristics of complex fractured pressure-sensitive reservoirs,and addresses a common technological problem,that is the alteration of the permeability degree of the reservoir bed(known to be responsible for changes in the direction and velocity of fluid flows between wells).On the basis of a new pressuresensitive equation that considers the fracture directional pressure-sensitive effect,an oil-gas-water three-phase seepage mathematical model is introduced,which can be applied to pressure-sensitive,full-tensor permeability,ultralow-permeability reservoirs with fracture-induced anisotropy.Accordingly,numerical simulations are conducted to explore the seepage laws for ultralow-permeability reservoirs.The results show that element patterns have the highest recovery percentage under a fracture angle of 45°.Accounting for the pressure-sensitive effect produces a decrease in the recovery percentage.Several patterns are considered:inverted five-seven-and nine-spot patterns and a cross-row well pattern.Finally,two strategies are introduced to counteract the rotation of the direction of the principal permeability due to the fracture directional pressure-sensitive effect.展开更多
Coherent change detection(CCD) is an effective method to detect subtle scene changes that occur between temporal synthetic aperture radar(SAR) observations. Most coherence estimators are obtained from a Hermitian prod...Coherent change detection(CCD) is an effective method to detect subtle scene changes that occur between temporal synthetic aperture radar(SAR) observations. Most coherence estimators are obtained from a Hermitian product based on local statistics. Increasing the number of samples in the local window can improve the estimation bias, but cause the loss of the estimated images spatial resolution. The limitations of these estimators lead to unclear contour of the disturbed region, and even the omission of fine change targets. In this paper, a CCD approach is proposed to detect fine scene changes from multi-temporal and multi-angle SAR image pairs. Multi-angle CCD estimator can improve the contrast between the change target and the background clutter by jointly accumulating singleangle alternative estimator results without further loss of image resolution. The sensitivity of detection performance to image quantity and angle interval is analyzed. Theoretical analysis and experimental results verify the performance of the proposed algorithm.展开更多
The objective of image-based virtual try-on is to seamlessly integrate clothing onto a target image, generating a realistic representation of the character in the specified attire. However, existing virtual try-on met...The objective of image-based virtual try-on is to seamlessly integrate clothing onto a target image, generating a realistic representation of the character in the specified attire. However, existing virtual try-on methods frequently encounter challenges, including misalignment between the body and clothing, noticeable artifacts, and the loss of intricate garment details. To overcome these challenges, we introduce a two-stage high-resolution virtual try-on framework that integrates an attention mechanism, comprising a garment warping stage and an image generation stage. During the garment warping stage, we incorporate a channel attention mechanism to effectively retain the critical features of the garment, addressing challenges such as the loss of patterns, colors, and other essential details commonly observed in virtual try-on images produced by existing methods. During the image generation stage, with the aim of maximizing the utilization of the information proffered by the input image, the input features undergo double sampling within the normalization procedure, thereby enhancing the detail fidelity and clothing alignment efficacy of the output image. Experimental evaluations conducted on high-resolution datasets validate the effectiveness of the proposed method. Results demonstrate significant improvements in preserving garment details, reducing artifacts, and achieving superior alignment between the clothing and body compared to baseline methods, establishing its advantage in generating realistic and high-quality virtual try-on images.展开更多
Improving customer experience has become a more and more important role in enhancing customer service in fashion retailing business. In this study, a kind of intelligent garment coordination and try-on system for fash...Improving customer experience has become a more and more important role in enhancing customer service in fashion retailing business. In this study, a kind of intelligent garment coordination and try-on system for fashion retailing was proposed. Radio Frequency Identification （RFID） technology was used to identify customer and garment item automatically. The intelligent procedure for garment coordination recommendation using Artificial Neural Network （ANN） was developed to imitate fashion designers＇ decision-making on garment coordination. Virtual try-on algorithm based on the customer＇s 2D/mago was accomplished using imagewarping technique. The system architecture and the software framework were also described. The results show that the ＇system is a practical and useful application for fashion retailers.展开更多
After carefully studying the results of retrieval of land surface temperature(LST) by multi-channel thermal infrared remote sensing data, the authors of this paper point out that its accuracy and significance for appl...After carefully studying the results of retrieval of land surface temperature(LST) by multi-channel thermal infrared remote sensing data, the authors of this paper point out that its accuracy and significance for applications are seriously damaged by the high correlation coefficient among multi-channel information and its disablement of direct retrieval of component temperature. Based on the model of directional radiation of non-isothermal mixed pixel, the authors point out that multi-angle thermal infrared remote sensing can offer the possibility to directly retrieve component temperature, but it is also a multi-parameter synchronous inverse problem. The results of digital simulation and field experiments show that the genetic inverse algorithm (GIA) is an effective method to fulfill multi-parameter synchronous retrieval. So it is possible to realize retrieval of component temperature with error less than 1K by multi-angle thermal infrared remote sensing data and GIA.展开更多
An algorithm to retrieve aerosol optical properties using multi-angular,multi-spectral,and polarized data without a priori knowledge of the land surface was developed.In the algorithm,the surface polarized reflectance...An algorithm to retrieve aerosol optical properties using multi-angular,multi-spectral,and polarized data without a priori knowledge of the land surface was developed.In the algorithm,the surface polarized reflectance was estimated by eliminating the atmospheric scattering from measured polarized reflectance at 1640 nm.A lookup table （LUT） and an iterative method were adopted in the algorithm to retrieve the aerosol optical thickness （AOT,at 665 nm） and the （A）ngstr（o）m exponent （computed between the AOTs at 665 and 865 nm）.Experiments were performed in Tianjin to verify the algorithm.Data were provided by a newly developed airborne instrument,the Advanced Atmosphere Multi-angle Polarization Radiometer （AMPR）.The AMPR measurements over the target field agreed well with the nearby ground-based sun photometer.An algorithm based on Research Scanning Polarimeter （RSP） measurements was introduced to validate the observational measurements along a flight path over Tianjin.The retrievals were consistent between the two algorithms.The AMPR algorithm shows potential in retrieving aerosol optical properties over a vegetation surface.展开更多
With the wavelet transform,image of multi-angle remote sensing is decomposed into multi-resolution.With data of each resolution,we try target-based multi-stages inversion,taking the inversion result of coarse resoluti...With the wavelet transform,image of multi-angle remote sensing is decomposed into multi-resolution.With data of each resolution,we try target-based multi-stages inversion,taking the inversion result of coarse resolution as the prior information of the next inversion.The result gets finer and finer until the resolution of satellite observation.In this way,the target-based multi-stages inversion can be used in remote sensing inversion of large-scaled coverage.With MISR data,we inverse structure parameters of vegetation in semiarid grassland of the Inner Mongolia Autonomous Region.The result proves that this way is efficient.展开更多
The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satell...The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satellite observations, the spatio-temporal characteristics of MILS_BRF data have rarely been explicitly and comprehensively analysed. Results from 5-yr(2011–2015) of MILS_BRF dataset from a typical region in central Northeast Asia as the study area showed that the monthly area coverage as well as MILS_BRF data quantity varies significantly, from the highest in October(99.05%) through median in June/July(78.09%/75.21%) to lowest in January(18.97%), and a large data-vacant area exists in the study area during four consecutive winter months(December through March). The data-vacant area is mainly composed of crop lands and cropland/natural vegetation mosaic. The amount of data within the principal plane(PP)±30°(nPP) or cross PP ±30°(nCP), varies intra-annually with significant differences from different view zeniths or forward/backward scattering directions. For example, multiple off-nadir cameras have nPP but no nCP data for up to six months(September through February), with the opposite occurring in June and July. This study provides explicit and comprehensive information about the spatio-temporal characteristics of product coverage and observation geometry of MILS_BRF in the study area. Results provide required user reference information for MILS_BRF to evaluate performance of BRDF models or to compare with other satellite-derived BRF or albedo products. Comparing this final product to on-satellite observations, what was found here reveals a new perspective on product spatial coverage and observation geometry for multi-angle remote sensing.展开更多
On the basis of the multi-angle polarized reflection spectrum of the water samples,the water body mirror reflection polarization characteristics and mechanism are described systematically. By altering such influential...On the basis of the multi-angle polarized reflection spectrum of the water samples,the water body mirror reflection polarization characteristics and mechanism are described systematically. By altering such influential factors as the angle of incidence,detecting angle,detecting azimuth angle and polari-zation angle,ubiquitous laws for the multi-angle polarized reflection spectrum of the water samples are obtained. Combining multi-angle remote sensing with polarized light,the multi-angle polarized reflec-tion method about eliminating the water body mirror reflection and the suitable time of the polarized remote sensing of the water body are proposed. This study provides technical references for the ap-plication of multi-angle polarization technology on water body remote sensing.展开更多
A panorama can reflect the surrounding scenery because it is an image with a wide angle of view.It can be applied in virtual reality,smart homes and other fields as well.A multi-directional reconstruction algorithm fo...A panorama can reflect the surrounding scenery because it is an image with a wide angle of view.It can be applied in virtual reality,smart homes and other fields as well.A multi-directional reconstruction algorithm for panoramic camera is proposed in this paper according to the imaging principle of dome camera,as the distortion inevitably exists in the captured panorama.First,parameters of a panoramic image are calculated.Then,a weighting operator with location information is introduced to solve the problem of rough edges by taking full advantage of pixels.Six directions of the mapping model are built,which include up,down,left,right,front and back,according to the correspondence between cylinder and spherical coordinates.Finally,multi-directional image reconstruction can be realized.Various experiments are performed in panoramas(1024×1024)with 30 different shooting scenes.Results show that the azimuth image can be reconstructed quickly and accurately.The fuzzy edge can be alleviated effectively.The rate of pixel utilization can reach 84%,and it is 33%higher than the direct mapping algorithm.Large scale distortion is also further studied.展开更多
A Local Ensemble Transform Kalman Filter assimilation system has been implemented into an aerosol-coupled global nonhydrostatic model to simulate the aerosol mass concentration and aerosol optical properties of 3 dese...A Local Ensemble Transform Kalman Filter assimilation system has been implemented into an aerosol-coupled global nonhydrostatic model to simulate the aerosol mass concentration and aerosol optical properties of 3 desert sites(Ansai, Fukang, Shapotou) in northwestern China. One-month experiment results of April 2006 reveal that the data assimilation can correct the much overestimated aerosol surface mass concentration, and has a strong positive effect on the aerosol optical depth(AOD) simulation, improving agreement with observations. Improvement is limited with the?ngstr€om Exponent(AE) simulation, except for much improved correlation coefficient and model skill scores over the Ansai site. Better agreement of the AOD spatial distribution with the independent observations of Terra(Deep Blue) and Multi-angle Imaging Spectroradiometer(MISR) AODs is obtained by assimilating the Moderate Resolution Imaging Spectroradiometer(MODIS) AOD product, especially for regions with AODs lower than 0.30. This study confirms the usefulness of the remote sensing observations for the improvement of global aerosol modeling.展开更多
At present,the Chinese economy has already begun shifting from its previous stage of rapid growth to a new stage of high-quality development. I.The inevitability of the shift toward high-quality development 1.The shif...At present,the Chinese economy has already begun shifting from its previous stage of rapid growth to a new stage of high-quality development. I.The inevitability of the shift toward high-quality development 1.The shift toward high-quality development is an objective re- quirement as Chinas economy enters a new era,along with the advance of Chinese socialism.展开更多
In the recent days, the segmentation of Liver Tumor (LT) has beendemanding and challenging. The process of segmenting the liver and accuratelyspotting the tumor is demanding due to the diversity of shape, texture, and...In the recent days, the segmentation of Liver Tumor (LT) has beendemanding and challenging. The process of segmenting the liver and accuratelyspotting the tumor is demanding due to the diversity of shape, texture, and intensity of the liver image. The intensity similarities of the neighboring organs of theliver create difficulties during liver segmentation. The manual segmentation doesnot provide an accurate segmentation because the results provided by differentmedical experts can vary. Also, this manual technique requires a large numberof image slices and time for segmentation. To solve these issues, the Fully Automatic Segmentation (FAS) technique is proposed. In this proposed Multi-AngleTexture Active Contour Model (MAT-ACM) method, the input Computed Tomography (CT) image is preprocessed by Contrast Enhancement (CE) with Non-Linear Mapping Technique (NLMT), in which the liver is differentiated from itsneighbouring soft tissues with related strength. Then, the filtered images are givenas the input to Adaptive Edge Modeling (AEM) with Canny Edge Detection(CED) technique, which segments the Liver Region (LR) from the given CTimages. An AEM with a CED model is implemented, which increases the convergence speed of the iterative process for decreasing the Volumetric Overlap Error(VOE) is 6.92% rates when compared with the traditional Segmentation Techniques (ST). Finally, the Liver Tumor Segmentation (LTS) is developed by applyingthe MAT-ACM, which accurately segments the LR from the segmented LRs. Theevaluation of the proposed method is compared with the existing LTS methodsusing various performance measures to prove the superiority of the proposedMAT-ACM method.展开更多
基金supported by the National Natural Science Foundation of China(No.72071150)the Fujian Provincial Natural Science Foundation of China(Nos.2024J01903,2025J01393).
文摘For the past few years,the prevalence of cardiovascular disease has been showing a year-on-year increase,with a death rate of 2/5.Coronary heart disease(CHD)rates have increased 41%since 1990,which is the number one disease endangering human health in the world today.The risk indicators of CHD are complicated,so selecting effective methods to screen the risk characteristics can make the risk predictionmore efficient.In this paper,we present a comprehensive analysis ofCHDrisk indicators fromboth data and algorithmic levels,propose a method for CHDrisk indicator identification based on multi-angle integrated measurements and Sequential Backward Selection(SBS),and then build a risk prediction model.In the multi-angle integrated measurements stage,mRMR(Maximum Relevance Minimum Redundancy)is selected from the angle of feature correlation and redundancy of the dataset itself,SHAPRF(SHapley Additive exPlanations-Random Forest)is selected from the angle of interpretation of each feature to the results,and ARFS-RF(Algorithmic Randomness Feature Selection Random Forest)is selected from the angle of statistical interpretation of classification algorithm to measure the degree of feature importance.In the SBS stage,the features with low scores are deleted successively,and the accuracy of LightGBM(Light Gradient Boosting Machine)model is used as the evaluation index to select the final feature subset.This new risk assessment method is used to identify important factors affecting CHD,and the CHD dataset from the Kaggle website is used as the study subject.Finally,11 features are retained to construct a risk assessment indicator system for CHD.Using the LightGBM classifier as the core evaluationmetric,ourmethod achieved an accuracy of 0.8656 on the Kaggle CHD dataset(4238 samples,16 initial features),outperforming individual feature selection methods(mRMR,SHAP-RF,ARFS-RF)in both accuracy and feature reduction.This demonstrates the novelty and effectiveness of our multi-angle integrated measurement approach combined with SBS in building a concise yet highly predictive CHD risk model.
基金financially supported by the Fundamental Research Funds for the Central Universities,Sun Yat-sen University(Grant No.24qnpy041)the Science and Technology Innovation Key R&D Program of Chongqing(Grant No.CSTB2023TIAD-STX0030)。
文摘The electric vertical takeoff and landing(e VTOL)aircraft shows great potential for rapid military personnel deployment on the battlefield.However,its susceptibility to control loss,complex crashes,and extremely limited bottom energy-absorbing space demands higher comprehensive crashworthiness of its subfloor thin-walled structures.This study investigated the energy absorption capacity of novel concave polygonal carbon fiber reinforced plastics(CFRP)tubes under multi-angle collisions.Quasistatic compression experiments and finite element simulations were conducted to assess the failure mode and energy absorption.The influences of cross-section shapes,loading conditions,and geometry parameters on crashworthiness metrics were further analyzed.The results revealed that,under the similar weight,concave polygonal tubes exhibited superior energy absorption under axial loads compared to regular polygonal and circular tubes,attributed to the increased number of axial splits.However,both regular and concave polygonal tubes,particularly the latter,demonstrated reduced oblique energy absorption compared to traditional square tubes with the increasing ratio of SEA value decreased from 20%-16%.Notably,this reduction in energy absorption can be compensated for by the implementation of inward and outward crusher plugs,and with them,the concave polygonal tubes demonstrated outstanding overall crashworthiness performance under multiple loading conditions.This concave cross-sectional design methods could serve as a guidance for the development of the eVTOL subfloor.
基金National Key R&D Program of China(No.2019YFC1521300)。
文摘During the image generation phase,the parserfree Flow-Style-VTON model(PF-Flow-Style-VTON),which utilizes distilled appearance flows,faces two main challenges:blurring,deformation,occlusion,or loss of the arm or palm regions in the generated image when these regions of the person occlude the garment;blurring and deformation in the generated image when the person performs large pose movements and the target garment is complex with detailed patterns.To solve these two problems,an improved virtual try-on network model,denoted as IPF-Flow-Style-VTON,is proposed.Firstly,a target warped garment mask refinement module(M-RM)is introduced to refine the warped garment mask and remove erroneous information in the arm and palm regions,thereby improving the quality of subsequent image generation.Secondly,an improved global attention module(GAM)is integrated into the original image generation network,enhancing the ResUNet’s understanding of global context and optimizing the fusion of local features and global information,thereby further improving image generation quality.Finally,the UniPose model is used to provide the pose keypoint information of the target person image,guiding the task execution during the image generation phase.Experiments conducted on the VITON dataset show that the proposed method outperforms the original method,Flow-Style-VTON,by 5.4%,0.3%,6.7%,and 2.2%in Frchet inception distance(FID),structural similarity index measure(SSIM),learned perceptual image patch similarity(LPIPS),and peak signal-to-noise ratio(PSNR),respectively.Overall,the proposed method effectively improves upon the shortcomings of the original network and achieves better visual results.
基金supported by grants from the National High Technology Research and Development Program of China(2013AA102403)the National Natural Science Foundation of China (30921091, 31200274)+1 种基金the Program for New Century Excellent Talents in University (NCET-10-0386)the Fundamental Research Funds for the Central Universities (2013PY034, 2014BQ010)
文摘Plant phenomics has the potential to accelerate progress in understanding gene functions and environmental responses. Progress has been made in automating high-throughput plant phenotyping. However, few studies have investigated automated rice panicle counting. This paper describes a novel method for automatically and nonintrusively determining rice panicle numbers during the full heading stage by analyzing color images of rice plants taken from multiple angles. Pot-grown rice plants were transferred via an industrial conveyer to an imaging chamber. Color images from different angles were automatically acquired as a turntable rotated the plant. The images were then analyzed and the panicle number of each plant was determined. The image analysis pipeline consisted of extracting the i2 plane from the original color image, segmenting the image, discriminating the panicles from the rest of the plant using an artificial neural network, and calculating the panicle number in the current image. The panicle number of the plant was taken as the maximum of the panicle numbers extracted from all 12 multi-angle images. A total of 105 rice plants during the full heading stage were examined to test the performance of the method. The mean absolute error of the manual and automatic count was 0.5, with 95.3% of the plants yielding absolute errors within ± 1. The method will be useful for evaluating rice panicles and will serve as an important supplementary method for high-throughput rice phenotyping.
基金Project KZCX3-S W-338-1 supported by Science and Technology Innovation Foundation of Chinese Academy of Science and 49771057 supported by theNational Natural Science Foundation of China
文摘The traditional remote sensing mainly detects the ground vertically to obtain the 2D information but it is hard to get adequate parameters for the quantitative remote sensing to invert land features. The multi-angle observation can get more detailed and reliable 3D structural parameters of targets, so it makes the quantitative remote sensing applicable. During the process of reflecting, scattering and transmitting the electromagnetic wave, minerals and rocks could reveal the polarized features related to the nature of themselves. Therefore, it has become a new approach of quantitative remote sensing to detect multi-angle polarized information of minerals and rocks. In respect that the polarized reflectance always goes with the bidirectional one, we can obtain the 3D spatial distribution of targets by a polarized means together with detecting its bi-directional reflectance. From the perspective of multi-angle polarized remote sensing mechanism, the quantitative relationship between multi-angle polarized reflectance and the BRDF is studied in this paper. And it is testified that the bi-directional reflectance, polarized reflectance of 45° and the mean value of polarized reflectance are equal to that of the corresponding azimuth angle, zenith angle, detection angle and detection channels in 27t space by experiment.
基金supported by the National Natural Science Foundation of China(61801007)the Beijing Natural Science Foundation(4194075)。
文摘Ground-based synthetic aperture radar(GB-SAR) has been successfully applied to the ground deformation monitoring.However, due to the short length of the GB-SAR platform, the scope of observation is largely limited. The practical applications drive us to make improvements on the conventional linear rail GB-SAR system in order to achieve larger field imaging. First, a turntable is utilized to support the rotational movement of the radar.Next, a series of high-squint scanning is performed with multiple squint angles. Further, the high squint modulation phase of the echo data is eliminated. Then, a new multi-angle imaging method is performed in the wave number domain to expand the field of view. Simulation and real experiments verify the effectiveness of this method.
文摘Although important progresses have been already made in face detection,many false faces can be found in detection results and false detection rate is influenced by some factors,such as rotation and tilt of human face,complicated background,illumination,scale,cloak and hairstyle.This paper proposes a new method called DP-Adaboost algorithm to detect multi-angle human face and improve the correct detection rate.An improved Adaboost algorithm with the fusion of frontal face classifier and a profile face classifier is used to detect the multi-angle face.An improved horizontal differential projection algorithm is put forward to remove those non-face images among the preliminary detection results from the improved Adaboost algorithm.Experiment results show that compared with the classical Adaboost algorithm with a frontal face classifier,the textual DP-Adaboost algorithm can reduce false rate significantly and improve hit rate in multi-angle face detection.
基金This work is financially supported by the National Natural Science Foundation Project(No.51374222)National Major Project(No.2017ZX05032004-002)+2 种基金the National Key Basic Research&Development Program(No.2015CB250905)CNPC’s Major Scientific and Technological Project(No.2017E-0405)SINOPEC Major Scientific Research Project(No.P18049-1).
文摘This study clarifies the seepage characteristics of complex fractured pressure-sensitive reservoirs,and addresses a common technological problem,that is the alteration of the permeability degree of the reservoir bed(known to be responsible for changes in the direction and velocity of fluid flows between wells).On the basis of a new pressuresensitive equation that considers the fracture directional pressure-sensitive effect,an oil-gas-water three-phase seepage mathematical model is introduced,which can be applied to pressure-sensitive,full-tensor permeability,ultralow-permeability reservoirs with fracture-induced anisotropy.Accordingly,numerical simulations are conducted to explore the seepage laws for ultralow-permeability reservoirs.The results show that element patterns have the highest recovery percentage under a fracture angle of 45°.Accounting for the pressure-sensitive effect produces a decrease in the recovery percentage.Several patterns are considered:inverted five-seven-and nine-spot patterns and a cross-row well pattern.Finally,two strategies are introduced to counteract the rotation of the direction of the principal permeability due to the fracture directional pressure-sensitive effect.
文摘Coherent change detection(CCD) is an effective method to detect subtle scene changes that occur between temporal synthetic aperture radar(SAR) observations. Most coherence estimators are obtained from a Hermitian product based on local statistics. Increasing the number of samples in the local window can improve the estimation bias, but cause the loss of the estimated images spatial resolution. The limitations of these estimators lead to unclear contour of the disturbed region, and even the omission of fine change targets. In this paper, a CCD approach is proposed to detect fine scene changes from multi-temporal and multi-angle SAR image pairs. Multi-angle CCD estimator can improve the contrast between the change target and the background clutter by jointly accumulating singleangle alternative estimator results without further loss of image resolution. The sensitivity of detection performance to image quantity and angle interval is analyzed. Theoretical analysis and experimental results verify the performance of the proposed algorithm.
基金supported by the National Natural Science Foundation of China(61772179)Hunan Provincial Natural Science Foundation of China(2022JJ50016,2023JJ50095)+1 种基金the Science and Technology Plan Project of Hunan Province(2016TP1020)Double First-Class University Project of Hunan Province(Xiangjiaotong[2018]469,[2020]248).
文摘The objective of image-based virtual try-on is to seamlessly integrate clothing onto a target image, generating a realistic representation of the character in the specified attire. However, existing virtual try-on methods frequently encounter challenges, including misalignment between the body and clothing, noticeable artifacts, and the loss of intricate garment details. To overcome these challenges, we introduce a two-stage high-resolution virtual try-on framework that integrates an attention mechanism, comprising a garment warping stage and an image generation stage. During the garment warping stage, we incorporate a channel attention mechanism to effectively retain the critical features of the garment, addressing challenges such as the loss of patterns, colors, and other essential details commonly observed in virtual try-on images produced by existing methods. During the image generation stage, with the aim of maximizing the utilization of the information proffered by the input image, the input features undergo double sampling within the normalization procedure, thereby enhancing the detail fidelity and clothing alignment efficacy of the output image. Experimental evaluations conducted on high-resolution datasets validate the effectiveness of the proposed method. Results demonstrate significant improvements in preserving garment details, reducing artifacts, and achieving superior alignment between the clothing and body compared to baseline methods, establishing its advantage in generating realistic and high-quality virtual try-on images.
基金National Nature Science Foundations of China (No.60975059, No.60775052)Specialized Research Fund for the Doctoral Program of Higher Education from Ministry of Education of China (No.20090075110002)Projects of Shanghai Committee of Science and Technology, China (No.09JC1400900, No.08JC1400100, No.10DZ0506500)
文摘Improving customer experience has become a more and more important role in enhancing customer service in fashion retailing business. In this study, a kind of intelligent garment coordination and try-on system for fashion retailing was proposed. Radio Frequency Identification （RFID） technology was used to identify customer and garment item automatically. The intelligent procedure for garment coordination recommendation using Artificial Neural Network （ANN） was developed to imitate fashion designers＇ decision-making on garment coordination. Virtual try-on algorithm based on the customer＇s 2D/mago was accomplished using imagewarping technique. The system architecture and the software framework were also described. The results show that the ＇system is a practical and useful application for fashion retailers.
基金China National Key-Important Basic Research Plan (Grant No. 95-Y-38) and the Special Funds for Major State Basic Research Project (Grant No. 20000779900).
文摘After carefully studying the results of retrieval of land surface temperature(LST) by multi-channel thermal infrared remote sensing data, the authors of this paper point out that its accuracy and significance for applications are seriously damaged by the high correlation coefficient among multi-channel information and its disablement of direct retrieval of component temperature. Based on the model of directional radiation of non-isothermal mixed pixel, the authors point out that multi-angle thermal infrared remote sensing can offer the possibility to directly retrieve component temperature, but it is also a multi-parameter synchronous inverse problem. The results of digital simulation and field experiments show that the genetic inverse algorithm (GIA) is an effective method to fulfill multi-parameter synchronous retrieval. So it is possible to realize retrieval of component temperature with error less than 1K by multi-angle thermal infrared remote sensing data and GIA.
基金supported by the Chinese Airborne Remote Sensing System, the Major National Science and Technology Infrastructure Construction Projectsthe Key Programs of the Chinese Academy of Sciences (Grant No. KGFZD125-13-006)
文摘An algorithm to retrieve aerosol optical properties using multi-angular,multi-spectral,and polarized data without a priori knowledge of the land surface was developed.In the algorithm,the surface polarized reflectance was estimated by eliminating the atmospheric scattering from measured polarized reflectance at 1640 nm.A lookup table （LUT） and an iterative method were adopted in the algorithm to retrieve the aerosol optical thickness （AOT,at 665 nm） and the （A）ngstr（o）m exponent （computed between the AOTs at 665 and 865 nm）.Experiments were performed in Tianjin to verify the algorithm.Data were provided by a newly developed airborne instrument,the Advanced Atmosphere Multi-angle Polarization Radiometer （AMPR）.The AMPR measurements over the target field agreed well with the nearby ground-based sun photometer.An algorithm based on Research Scanning Polarimeter （RSP） measurements was introduced to validate the observational measurements along a flight path over Tianjin.The retrievals were consistent between the two algorithms.The AMPR algorithm shows potential in retrieving aerosol optical properties over a vegetation surface.
基金the National Key Basic Research Project of China(Grant No.G2000077907)the National Natural Science Foundation of China(Grant No.40271082)
文摘With the wavelet transform,image of multi-angle remote sensing is decomposed into multi-resolution.With data of each resolution,we try target-based multi-stages inversion,taking the inversion result of coarse resolution as the prior information of the next inversion.The result gets finer and finer until the resolution of satellite observation.In this way,the target-based multi-stages inversion can be used in remote sensing inversion of large-scaled coverage.With MISR data,we inverse structure parameters of vegetation in semiarid grassland of the Inner Mongolia Autonomous Region.The result proves that this way is efficient.
基金Under the auspices the Fundamental Research Funds for the Central Universities,China(No.2017TD-26)the Plan for Changbai Mountain Scholars of Jilin Province,China(No.JJLZ[2015]54)
文摘The Multi-angle imaging spectroradiometer(MISR) land-surface(LS) bidirectional reflectance factor(BRF) product(MILS_BRF) has unique semi-simultaneous multi-angle sampling and global coverage. However, unlike on-satellite observations, the spatio-temporal characteristics of MILS_BRF data have rarely been explicitly and comprehensively analysed. Results from 5-yr(2011–2015) of MILS_BRF dataset from a typical region in central Northeast Asia as the study area showed that the monthly area coverage as well as MILS_BRF data quantity varies significantly, from the highest in October(99.05%) through median in June/July(78.09%/75.21%) to lowest in January(18.97%), and a large data-vacant area exists in the study area during four consecutive winter months(December through March). The data-vacant area is mainly composed of crop lands and cropland/natural vegetation mosaic. The amount of data within the principal plane(PP)±30°(nPP) or cross PP ±30°(nCP), varies intra-annually with significant differences from different view zeniths or forward/backward scattering directions. For example, multiple off-nadir cameras have nPP but no nCP data for up to six months(September through February), with the opposite occurring in June and July. This study provides explicit and comprehensive information about the spatio-temporal characteristics of product coverage and observation geometry of MILS_BRF in the study area. Results provide required user reference information for MILS_BRF to evaluate performance of BRDF models or to compare with other satellite-derived BRF or albedo products. Comparing this final product to on-satellite observations, what was found here reveals a new perspective on product spatial coverage and observation geometry for multi-angle remote sensing.
基金the Science and Technology Foundation of CAS (Grant No. KZCX3-SW-338-1)the National Natural Science Foundation of China (Grant No. 49771057)
文摘On the basis of the multi-angle polarized reflection spectrum of the water samples,the water body mirror reflection polarization characteristics and mechanism are described systematically. By altering such influential factors as the angle of incidence,detecting angle,detecting azimuth angle and polari-zation angle,ubiquitous laws for the multi-angle polarized reflection spectrum of the water samples are obtained. Combining multi-angle remote sensing with polarized light,the multi-angle polarized reflec-tion method about eliminating the water body mirror reflection and the suitable time of the polarized remote sensing of the water body are proposed. This study provides technical references for the ap-plication of multi-angle polarization technology on water body remote sensing.
基金This work is supported by Light of West China(Grant No.XAB2016B23)Chinese Academy of Sciences.And the Open Project Program of the State Key Lab of CAD&CG(Grant No.A2026),Zhejiang University.
文摘A panorama can reflect the surrounding scenery because it is an image with a wide angle of view.It can be applied in virtual reality,smart homes and other fields as well.A multi-directional reconstruction algorithm for panoramic camera is proposed in this paper according to the imaging principle of dome camera,as the distortion inevitably exists in the captured panorama.First,parameters of a panoramic image are calculated.Then,a weighting operator with location information is introduced to solve the problem of rough edges by taking full advantage of pixels.Six directions of the mapping model are built,which include up,down,left,right,front and back,according to the correspondence between cylinder and spherical coordinates.Finally,multi-directional image reconstruction can be realized.Various experiments are performed in panoramas(1024×1024)with 30 different shooting scenes.Results show that the azimuth image can be reconstructed quickly and accurately.The fuzzy edge can be alleviated effectively.The rate of pixel utilization can reach 84%,and it is 33%higher than the direct mapping algorithm.Large scale distortion is also further studied.
基金supported by the funds from the National Natural Science Funds of China (41475031, 41130104)the Public Meteorology Special Foundation of MOST (GYHY201406023)+1 种基金the special fund of State Key Joint Laboratory of Environment Simulation and Pollution Control(15K02ESPCP)the JAXA/Earth CARE, the MEXT/VL for Climate System Diagnostics, the MOE/Global Environment Research Fund S-12 (14426634)and A-1101, the NIES/GOSAT, theS/ NIECGER, and the MEXT/RECCA/SALSA
文摘A Local Ensemble Transform Kalman Filter assimilation system has been implemented into an aerosol-coupled global nonhydrostatic model to simulate the aerosol mass concentration and aerosol optical properties of 3 desert sites(Ansai, Fukang, Shapotou) in northwestern China. One-month experiment results of April 2006 reveal that the data assimilation can correct the much overestimated aerosol surface mass concentration, and has a strong positive effect on the aerosol optical depth(AOD) simulation, improving agreement with observations. Improvement is limited with the?ngstr€om Exponent(AE) simulation, except for much improved correlation coefficient and model skill scores over the Ansai site. Better agreement of the AOD spatial distribution with the independent observations of Terra(Deep Blue) and Multi-angle Imaging Spectroradiometer(MISR) AODs is obtained by assimilating the Moderate Resolution Imaging Spectroradiometer(MODIS) AOD product, especially for regions with AODs lower than 0.30. This study confirms the usefulness of the remote sensing observations for the improvement of global aerosol modeling.
文摘At present,the Chinese economy has already begun shifting from its previous stage of rapid growth to a new stage of high-quality development. I.The inevitability of the shift toward high-quality development 1.The shift toward high-quality development is an objective re- quirement as Chinas economy enters a new era,along with the advance of Chinese socialism.
基金funded by Dirección General de Investigaciones of Universidad Santiago de Cali under call No.01-2021.
文摘In the recent days, the segmentation of Liver Tumor (LT) has beendemanding and challenging. The process of segmenting the liver and accuratelyspotting the tumor is demanding due to the diversity of shape, texture, and intensity of the liver image. The intensity similarities of the neighboring organs of theliver create difficulties during liver segmentation. The manual segmentation doesnot provide an accurate segmentation because the results provided by differentmedical experts can vary. Also, this manual technique requires a large numberof image slices and time for segmentation. To solve these issues, the Fully Automatic Segmentation (FAS) technique is proposed. In this proposed Multi-AngleTexture Active Contour Model (MAT-ACM) method, the input Computed Tomography (CT) image is preprocessed by Contrast Enhancement (CE) with Non-Linear Mapping Technique (NLMT), in which the liver is differentiated from itsneighbouring soft tissues with related strength. Then, the filtered images are givenas the input to Adaptive Edge Modeling (AEM) with Canny Edge Detection(CED) technique, which segments the Liver Region (LR) from the given CTimages. An AEM with a CED model is implemented, which increases the convergence speed of the iterative process for decreasing the Volumetric Overlap Error(VOE) is 6.92% rates when compared with the traditional Segmentation Techniques (ST). Finally, the Liver Tumor Segmentation (LTS) is developed by applyingthe MAT-ACM, which accurately segments the LR from the segmented LRs. Theevaluation of the proposed method is compared with the existing LTS methodsusing various performance measures to prove the superiority of the proposedMAT-ACM method.
