The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Let...The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.展开更多
The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Let...The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.展开更多
The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Let...The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.展开更多
The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Let...The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.展开更多
Optoelectronics Letters accepts Word style submissions.The title,author listing,captions for figures and tables should be in Arial font.The rest of the text and body of the article should be in Times New Roman font.
Optoelectronics Letters accepts Word style submissions.The title,author listing,captions for figures and tables should be in Arial font.The rest of the text and body of the article should be in Times New Roman font.
The goal of Optoelectronics Letters is to rapidly report original, new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges. Optoelectronics L...The goal of Optoelectronics Letters is to rapidly report original, new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges. Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.展开更多
The goal of Optoelectronics Letters is to rapidly report original, new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges. Optoelectronics L...The goal of Optoelectronics Letters is to rapidly report original, new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges. Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.展开更多
Current you only look once(YOLO)-based algorithm model is facing the challenge of overwhelming parameters and calculation complexity under the printed circuit board(PCB)defect detection application scenario.In order t...Current you only look once(YOLO)-based algorithm model is facing the challenge of overwhelming parameters and calculation complexity under the printed circuit board(PCB)defect detection application scenario.In order to solve this problem,we propose a new method,which combined the lightweight network mobile vision transformer(Mobile Vi T)with the convolutional block attention module(CBAM)mechanism and the new regression loss function.This method needed less computation resources,making it more suitable for embedded edge detection devices.Meanwhile,the new loss function improved the positioning accuracy of the bounding box and enhanced the robustness of the model.In addition,experiments on public datasets demonstrate that the improved model achieves an average accuracy of 87.9%across six typical defect detection tasks,while reducing computational costs by nearly 90%.It significantly reduces the model's computational requirements while maintaining accuracy,ensuring reliable performance for edge deployment.展开更多
In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering...In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering correction(MSC)-maximum-minimum normalization(MN)was identified as the optimal preprocessing technique.The competitive adaptive reweighted sampling(CARS),successive projections algorithm(SPA),and their combined methods were employed to extract feature wavelengths.Classification models based on back propagation(BP),support vector machine(SVM),random forest(RF),and partial least squares(PLS)were established using full-band data and feature wavelengths.Among all models,the(CARS-SPA)-BP model achieved the highest accuracy rate of 98.44%.This study offers novel insights and methodologies for the rapid and accurate identification of corn seeds as well as other crop seeds.展开更多
In this paper, we have demonstrated an Er-doped ultrafast laser with a single mode fiber-gradient index multimode fiber-single mode fiber(SMF-GIMF-SMF, SMS) structure as saturable absorber(SA), which can generate not ...In this paper, we have demonstrated an Er-doped ultrafast laser with a single mode fiber-gradient index multimode fiber-single mode fiber(SMF-GIMF-SMF, SMS) structure as saturable absorber(SA), which can generate not only stable single-pulse state, but also special mode-locked pulses with the characteristics of high energy and noisy behaviors at proper pump power and cavity polarization state. In addition, we have deeply investigated the real-time spectral evolutions of the mode-locked pulses through the dispersive Fourier transformation(DFT) technique. It can be found that the pulse regime can actually consist of a lot of small noise pulses with randomly varying intensities. We believe that these results will further enrich the nonlinear dynamical processes in the ultrafast lasers.展开更多
An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyram...An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyramid network(FPN)structure of the original YOLOv8 mode is replaced by the generalized-FPN(GFPN)structure in GiraffeDet to realize the"cross-layer"and"cross-scale"adaptive feature fusion,to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model.Secondly,a pyramid-pool module of multi atrous spatial pyramid pooling(MASPP)is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features,so as to improve the processing ability of the model for multi-scale objects.The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92%and mean average precision(mAP)is 87.9%,respectively 3.5%and 1.7%higher than those of the original model.It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved.展开更多
This paper demonstrated the generation of multi-wavelength bound state noise-like pulse(BNLP)in a dispersion-managed composite-filtered fiber laser consisting of nonlinear polarization rotation(NPR)and loop.In the cas...This paper demonstrated the generation of multi-wavelength bound state noise-like pulse(BNLP)in a dispersion-managed composite-filtered fiber laser consisting of nonlinear polarization rotation(NPR)and loop.In the case of BNLP,the generation is caused by the interaction between two noise-like pulses(NLPs)induced by the comb-filtering effect,and bound state level can be artificially controlled in the researches.Our work provides a new method for generating low-coherence pulses and establishes a research idea for the study of the comb-filtering effects.展开更多
Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time perfor...Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.展开更多
The unmanned aerial vehicle(UAV)images captured under low-light conditions are often suffering from noise and uneven illumination.To address these issues,we propose a low-light image enhancement algorithm for UAV imag...The unmanned aerial vehicle(UAV)images captured under low-light conditions are often suffering from noise and uneven illumination.To address these issues,we propose a low-light image enhancement algorithm for UAV images,which is inspired by the Retinex theory and guided by a light weighted map.Firstly,we propose a new network for reflectance component processing to suppress the noise in images.Secondly,we construct an illumination enhancement module that uses a light weighted map to guide the enhancement process.Finally,the processed reflectance and illumination components are recombined to obtain the enhancement results.Experimental results show that our method can suppress the noise in images while enhancing image brightness,and prevent over enhancement in bright regions.Code and data are available at https://gitee.com/baixiaotong2/uav-images.git.展开更多
This paper proposes a lightweight traffic sign detection system based on you only look once(YOLO).Firstly,the classification to fusion(C2f)structure is integrated into the backbone network,employing deformable convolu...This paper proposes a lightweight traffic sign detection system based on you only look once(YOLO).Firstly,the classification to fusion(C2f)structure is integrated into the backbone network,employing deformable convolution and bi-directional feature pyramid network(BiFPN)_Concat to improve the adaptability of the network.Secondly,the simple attention module(SimAm)is embedded to prioritize key features and reduce the complexity of the model after the C2f layer at the end of the backbone network.Next,the focal efficient intersection over union(EloU)is introduced to adjust the weights of challenging samples.Finally,we accomplish the design and deployment for the mobile app.The results demonstrate improvements,with the F1 score of 0.8987,mean average precision(mAP)@0.5 of 98.8%,mAP@0.5:0.95 of 75.6%,and the detection speed of 50 frames per second(FPS).展开更多
The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions a...The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.展开更多
Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework f...Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.展开更多
Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse de...Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds.Building on this concept,we propose a novel framework,building extraction diffusion model(BEDiff),which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion.Our approach begins with the design of booster guidance,a mechanism that extracts structural and semantic features from remote sensing images to serve as priors,thereby providing targeted guidance for the diffusion process.Additionally,we introduce a cross-feature fusion module(CFM)that bridges the semantic gap between different types of features,facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively.Our proposed BEDiff marks the first application of diffusion models to the task of building extraction.Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff,affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.展开更多
Cu_(2)ZnSn(S,Se)_(4)(CZTSSe)is considered to be the most potential light-absorbing material to replace CuInGaSe_(2)(CIGS),but the actual photoelectric conversion efficiency of such cells is much lower than that of CIG...Cu_(2)ZnSn(S,Se)_(4)(CZTSSe)is considered to be the most potential light-absorbing material to replace CuInGaSe_(2)(CIGS),but the actual photoelectric conversion efficiency of such cells is much lower than that of CIGS.One of the reasons is the high recombination rate of carriers at the interface.In this paper,in order to reduce the carrier recombination,a new solar cell structure with double absorber layers of Al-doped ZnO(AZO)/intrinsic(i)-ZnO/CdS/CZTS_(x1)Se_(1−x1)(CZTSSe_(1))/CZTS_(x2)Se_(1−x2)(CZTSSe_(2))/Mo was proposed,and the optimal conduction band offsets(CBOs)of CdS/CZTSSe_(1) interface and CZTSSe_(1)/CZTSSe_(2) interface were determined by changing the S ratio in CZTSSe_(1) and CZTSSe_(2),and the effect of thickness of CZTSSe_(1) on the performance of the cell was studied.The efficiencies of the optimized single and double absorber layers reached 17.97%and 23.4%,respectively.Compared with the single absorber layer structure,the proposed structure with double absorber layers has better cell performance.展开更多
文摘The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.
文摘The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.
文摘The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.
文摘The goal of Optoelectronics Letters is to rapidly report original,new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges.Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.
文摘Optoelectronics Letters accepts Word style submissions.The title,author listing,captions for figures and tables should be in Arial font.The rest of the text and body of the article should be in Times New Roman font.
文摘Optoelectronics Letters accepts Word style submissions.The title,author listing,captions for figures and tables should be in Arial font.The rest of the text and body of the article should be in Times New Roman font.
文摘The goal of Optoelectronics Letters is to rapidly report original, new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges. Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.
文摘The goal of Optoelectronics Letters is to rapidly report original, new and important results in the fields of photonics and optoelectronics in English to advance the international academic exchanges. Optoelectronics Letters pays a particular attention to the cross topic between photonics and electronics.
基金supported by the National Natural Science Foundation of China(Nos.62373215,62373219 and 62073193)the Natural Science Foundation of Shandong Province(No.ZR2023MF100)+1 种基金the Key Projects of the Ministry of Industry and Information Technology(No.TC220H057-2022)the Independently Developed Instrument Funds of Shandong University(No.zy20240201)。
文摘Current you only look once(YOLO)-based algorithm model is facing the challenge of overwhelming parameters and calculation complexity under the printed circuit board(PCB)defect detection application scenario.In order to solve this problem,we propose a new method,which combined the lightweight network mobile vision transformer(Mobile Vi T)with the convolutional block attention module(CBAM)mechanism and the new regression loss function.This method needed less computation resources,making it more suitable for embedded edge detection devices.Meanwhile,the new loss function improved the positioning accuracy of the bounding box and enhanced the robustness of the model.In addition,experiments on public datasets demonstrate that the improved model achieves an average accuracy of 87.9%across six typical defect detection tasks,while reducing computational costs by nearly 90%.It significantly reduces the model's computational requirements while maintaining accuracy,ensuring reliable performance for edge deployment.
基金supported by the Science and Technology Development Plan Project of Jilin Provincial Department of Science and Technology (No.20220203112S)the Jilin Provincial Department of Education Science and Technology Research Project (No.JJKH20210039KJ)。
文摘In this study,eight different varieties of maize seeds were used as the research objects.Conduct 81 types of combined preprocessing on the original spectra.Through comparison,Savitzky-Golay(SG)-multivariate scattering correction(MSC)-maximum-minimum normalization(MN)was identified as the optimal preprocessing technique.The competitive adaptive reweighted sampling(CARS),successive projections algorithm(SPA),and their combined methods were employed to extract feature wavelengths.Classification models based on back propagation(BP),support vector machine(SVM),random forest(RF),and partial least squares(PLS)were established using full-band data and feature wavelengths.Among all models,the(CARS-SPA)-BP model achieved the highest accuracy rate of 98.44%.This study offers novel insights and methodologies for the rapid and accurate identification of corn seeds as well as other crop seeds.
基金supported by the Guangdong Basic and Applied Basic Research Foundation (No.2023A1515010093)the Shenzhen Fundamental Research Program (Stable Support Plan Program)(Nos.JCYJ20220809170611004, 20231121110828001 and 20231121113641002)the National Taipei University of Technology-Shenzhen University Joint Research Program (No.2024001)。
文摘In this paper, we have demonstrated an Er-doped ultrafast laser with a single mode fiber-gradient index multimode fiber-single mode fiber(SMF-GIMF-SMF, SMS) structure as saturable absorber(SA), which can generate not only stable single-pulse state, but also special mode-locked pulses with the characteristics of high energy and noisy behaviors at proper pump power and cavity polarization state. In addition, we have deeply investigated the real-time spectral evolutions of the mode-locked pulses through the dispersive Fourier transformation(DFT) technique. It can be found that the pulse regime can actually consist of a lot of small noise pulses with randomly varying intensities. We believe that these results will further enrich the nonlinear dynamical processes in the ultrafast lasers.
基金supported by the National Natural Science Foundation of China(No.62241109)the Tianjin Science and Technology Commissioner Project(No.20YDTPJC01110)。
文摘An improved model based on you only look once version 8(YOLOv8)is proposed to solve the problem of low detection accuracy due to the diversity of object sizes in optical remote sensing images.Firstly,the feature pyramid network(FPN)structure of the original YOLOv8 mode is replaced by the generalized-FPN(GFPN)structure in GiraffeDet to realize the"cross-layer"and"cross-scale"adaptive feature fusion,to enrich the semantic information and spatial information on the feature map to improve the target detection ability of the model.Secondly,a pyramid-pool module of multi atrous spatial pyramid pooling(MASPP)is designed by using the idea of atrous convolution and feature pyramid structure to extract multi-scale features,so as to improve the processing ability of the model for multi-scale objects.The experimental results show that the detection accuracy of the improved YOLOv8 model on DIOR dataset is 92%and mean average precision(mAP)is 87.9%,respectively 3.5%and 1.7%higher than those of the original model.It is proved the detection and classification ability of the proposed model on multi-dimensional optical remote sensing target has been improved.
基金supported by the Research Fund of Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology(No.2020B1212030010)。
文摘This paper demonstrated the generation of multi-wavelength bound state noise-like pulse(BNLP)in a dispersion-managed composite-filtered fiber laser consisting of nonlinear polarization rotation(NPR)and loop.In the case of BNLP,the generation is caused by the interaction between two noise-like pulses(NLPs)induced by the comb-filtering effect,and bound state level can be artificially controlled in the researches.Our work provides a new method for generating low-coherence pulses and establishes a research idea for the study of the comb-filtering effects.
基金supported by the National Key Research and Development Project of China(No.2023YFB3709605)the National Natural Science Foundation of China(No.62073193)the National College Student Innovation Training Program(No.202310422122)。
文摘Potential high-temperature risks exist in heat-prone components of electric moped charging devices,such as sockets,interfaces,and controllers.Traditional detection methods have limitations in terms of real-time performance and monitoring scope.To address this,a temperature detection method based on infrared image processing has been proposed:utilizing the median filtering algorithm to denoise the original infrared image,then applying an image segmentation algorithm to divide the image.
基金supported by the National Natural Science Foundation of China(Nos.62201454 and 62306235)the Xi’an Science and Technology Program of Xi’an Science and Technology Bureau(No.23SFSF0004)。
文摘The unmanned aerial vehicle(UAV)images captured under low-light conditions are often suffering from noise and uneven illumination.To address these issues,we propose a low-light image enhancement algorithm for UAV images,which is inspired by the Retinex theory and guided by a light weighted map.Firstly,we propose a new network for reflectance component processing to suppress the noise in images.Secondly,we construct an illumination enhancement module that uses a light weighted map to guide the enhancement process.Finally,the processed reflectance and illumination components are recombined to obtain the enhancement results.Experimental results show that our method can suppress the noise in images while enhancing image brightness,and prevent over enhancement in bright regions.Code and data are available at https://gitee.com/baixiaotong2/uav-images.git.
基金supported by the Shanxi Agricultural University Science and Technology Innovation Enhancement Project。
文摘This paper proposes a lightweight traffic sign detection system based on you only look once(YOLO).Firstly,the classification to fusion(C2f)structure is integrated into the backbone network,employing deformable convolution and bi-directional feature pyramid network(BiFPN)_Concat to improve the adaptability of the network.Secondly,the simple attention module(SimAm)is embedded to prioritize key features and reduce the complexity of the model after the C2f layer at the end of the backbone network.Next,the focal efficient intersection over union(EloU)is introduced to adjust the weights of challenging samples.Finally,we accomplish the design and deployment for the mobile app.The results demonstrate improvements,with the F1 score of 0.8987,mean average precision(mAP)@0.5 of 98.8%,mAP@0.5:0.95 of 75.6%,and the detection speed of 50 frames per second(FPS).
基金supported by the National Natural Science(No.U19A2063)the Jilin Provincial Development Program of Science and Technology (No.20230201080GX)the Jilin Province Education Department Scientific Research Project (No.JJKH20230851KJ)。
文摘The visual noise of each light intensity area is different when the image is drawn by Monte Carlo method.However,the existing denoising algorithms have limited denoising performance under complex lighting conditions and are easy to lose detailed information.So we propose a rendered image denoising method with filtering guided by lighting information.First,we design an image segmentation algorithm based on lighting information to segment the image into different illumination areas.Then,we establish the parameter prediction model guided by lighting information for filtering(PGLF)to predict the filtering parameters of different illumination areas.For different illumination areas,we use these filtering parameters to construct area filters,and the filters are guided by the lighting information to perform sub-area filtering.Finally,the filtering results are fused with auxiliary features to output denoised images for improving the overall denoising effect of the image.Under the physically based rendering tool(PBRT)scene and Tungsten dataset,the experimental results show that compared with other guided filtering denoising methods,our method improves the peak signal-to-noise ratio(PSNR)metrics by 4.2164 dB on average and the structural similarity index(SSIM)metrics by 7.8%on average.This shows that our method can better reduce the noise in complex lighting scenesand improvethe imagequality.
基金supported by the National Natural Science Foundation of China (No.62202137)the China Postdoctoral Science Foundation (No.2023M730599)the Zhejiang Provincial Natural Science Foundation of China (No.LMS25F020009)。
文摘Embodied visual exploration is critical for building intelligent visual agents. This paper presents the neural exploration with feature-based visual odometry and tracking-failure-reduction policy(Ne OR), a framework for embodied visual exploration that possesses the efficient exploration capabilities of deep reinforcement learning(DRL)-based exploration policies and leverages feature-based visual odometry(VO) for more accurate mapping and positioning results. An improved local policy is also proposed to reduce tracking failures of feature-based VO in weakly textured scenes through a refined multi-discrete action space, keyframe fusion, and an auxiliary task. The experimental results demonstrate that Ne OR has better mapping and positioning accuracy compared to other entirely learning-based exploration frameworks and improves the robustness of feature-based VO by significantly reducing tracking failures in weakly textured scenes.
基金supported by the National Natural Science Foundation of China(Nos.61906168,62202429 and 62272267)the Zhejiang Provincial Natural Science Foundation of China(No.LY23F020023)the Construction of Hubei Provincial Key Laboratory for Intelligent Visual Monitoring of Hydropower Projects(No.2022SDSJ01)。
文摘Accurately identifying building distribution from remote sensing images with complex background information is challenging.The emergence of diffusion models has prompted the innovative idea of employing the reverse denoising process to distill building distribution from these complex backgrounds.Building on this concept,we propose a novel framework,building extraction diffusion model(BEDiff),which meticulously refines the extraction of building footprints from remote sensing images in a stepwise fashion.Our approach begins with the design of booster guidance,a mechanism that extracts structural and semantic features from remote sensing images to serve as priors,thereby providing targeted guidance for the diffusion process.Additionally,we introduce a cross-feature fusion module(CFM)that bridges the semantic gap between different types of features,facilitating the integration of the attributes extracted by booster guidance into the diffusion process more effectively.Our proposed BEDiff marks the first application of diffusion models to the task of building extraction.Empirical evidence from extensive experiments on the Beijing building dataset demonstrates the superior performance of BEDiff,affirming its effectiveness and potential for enhancing the accuracy of building extraction in complex urban landscapes.
基金supported by the Science and Technology Innovation Development Program(No.70304901).
文摘Cu_(2)ZnSn(S,Se)_(4)(CZTSSe)is considered to be the most potential light-absorbing material to replace CuInGaSe_(2)(CIGS),but the actual photoelectric conversion efficiency of such cells is much lower than that of CIGS.One of the reasons is the high recombination rate of carriers at the interface.In this paper,in order to reduce the carrier recombination,a new solar cell structure with double absorber layers of Al-doped ZnO(AZO)/intrinsic(i)-ZnO/CdS/CZTS_(x1)Se_(1−x1)(CZTSSe_(1))/CZTS_(x2)Se_(1−x2)(CZTSSe_(2))/Mo was proposed,and the optimal conduction band offsets(CBOs)of CdS/CZTSSe_(1) interface and CZTSSe_(1)/CZTSSe_(2) interface were determined by changing the S ratio in CZTSSe_(1) and CZTSSe_(2),and the effect of thickness of CZTSSe_(1) on the performance of the cell was studied.The efficiencies of the optimized single and double absorber layers reached 17.97%and 23.4%,respectively.Compared with the single absorber layer structure,the proposed structure with double absorber layers has better cell performance.
