Chengdu teahouses,as core public spaces in marketplace society,have undergone transformative reconstruction-from“containers of everyday life”to“containers of commercial traffic and digital flows”-during the proces...Chengdu teahouses,as core public spaces in marketplace society,have undergone transformative reconstruction-from“containers of everyday life”to“containers of commercial traffic and digital flows”-during the process of modernization.Employing spatial archaeology as a methodology,combined with fieldwork and analysis of historical documents,this study systematically examines the diachronic evolution of architectural forms,functional orientations,and social networks within Chengdu teahouses.The study reveals the logic of spatial reconstruction under the interplay of multiple forces,including cultural heritage preservation,capital-driven development,and technological intervention.The findings identify three paradigms of spatial transformation in teahouses.First,heritage specimenization,which reinforces the continuity of collective memory through symbolic extraction but risks diminishing the vitality of everyday social interactions.Second,consumption upgrading,which caters to the demands of emerging groups through iterative business models yet necessitates vigilance against spatial differentiation eroding marketplace inclusivity.Third,digital parasitism,which expands communicative dimensions through technological empowerment but confronts the risk of flattening localized knowledge.These paradigms reflect both adaptive responses of traditional spaces to contemporary pressure and the tension of reconstruction imposed by instrumental rationality on marketplace networks.The study demonstrates that spatial transformation in Chengdu teahouses is not unidirectional alienation but rather a multifaceted configuration where the continuity of tradition coexists with innovative practices amid functional diversification.This research advocates for striking a balance between the preservation of traditional spaces and modern renewal and explores organic integration approaches for traditional and modern elements,thereby providing a theoretical framework and practical insights for the transformation of traditional public spaces.展开更多
Blade-health monitoring is intensely required for turbomachinery because of the high failure risk of rotating blades.Blade-Tip Timing(BTT)is considered as the most promising technique for operational blade-vibration m...Blade-health monitoring is intensely required for turbomachinery because of the high failure risk of rotating blades.Blade-Tip Timing(BTT)is considered as the most promising technique for operational blade-vibration monitoring,which obtains the parameters that characterize the blade condition from recorded signals.However,its application is hindered by severe undersampling and stringent probe layouts.An inappropriate probe layout can make most of the existing methods invalid or inaccurate.Additionally,a general conflict arises between the allowed and required layouts because of arrangement restrictions.For the sake of economy and safety,parameter identification based on fewer probes has been preferred by users.In this work,a spatial-transformation-based method for parameter identification is proposed based on a single-probe BTT measurement.To present the general Sampling-Aliasing Frequency(SAFE)map definition,the traditional time-frequency analysis methods are extended to a time-sampling frequency.Then,a SAFE map is projected onto a parameter space using spatial transformation to extract the slope and intercept parameters,which can be physically interpreted as an engine order and a natural frequency using coordinate transformation.Finally,the effectiveness and robustness of the proposed method are verified by simulations and experiments under uniformly and nonuniformly variable speed conditions.展开更多
The spatial transformations can be observed at different religious-historic towns of India due to urbanization. Research is based upon fact that there is substantial change in the built environment because of spatial ...The spatial transformations can be observed at different religious-historic towns of India due to urbanization. Research is based upon fact that there is substantial change in the built environment because of spatial transformations at the religious-historic towns. The process of modernization in the functions and spatial layout is unavoidable at any historic town. The study attempts to focus on various urban historic conservation components, including the look of historic buildings, their earlier uses, and its immediate surroundings to improve the built environment of historic towns. A theoretical framework for the urban conservation of ancient towns is the main objective of study. How to modernize the historic conservation function while preserving the space’s texture and integrity. The research started with the investigation of the morphological growth of Mathura district, India through satellite images and in-depth study of the evolution process of street network in Vrindavan town, which is one of the main temple towns of Mathura district. There is a significant difference in the layout & architectural character of old part and the newly developed Vrindavan. Due to increased accessibility and movement, the spatial structure of traditional religious precincts, which were once local integration centres, has significantly changed. Increasing & changing mode of transportation and further increase in the religious tourism might be the cause or a big reason for the spatial transformations and correspondingly there is a challenge to conserve & preserve the religious precincts of historic towns. The study tries to analyze spatial transformations with the help of Historical GIS at different scales of urban form. Suggestive measures to conserve the environmental ambience of religious-historic towns are the outcome of the research.展开更多
In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestri...In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestrian re-identification tasks,a person re-identification method combining spatial feature learning and multi-granularity feature fusion was proposed.First,an attention spatial transformation network(A-STN)is proposed to learn spatial features and solve the problem of misalignment of pedestrian spatial features.Then the network was divided into a global branch,a local coarse-grained fusion branch,and a local fine-grained fusion branch to extract pedestrian global features,coarse-grained fusion features,and fine-grained fusion features,respectively.Among them,the global branch enriches the global features by fusing different pooling features.The local coarse-grained fusion branch uses an overlay pooling to enhance each local feature while learning the correlation relationship between multi-granularity features.The local fine-grained fusion branch uses a differential pooling to obtain the differential features that were fused with global features to learn the relationship between pedestrian local features and pedestrian global features.Finally,the proposed method was compared on three public datasets:Market1501,DukeMTMC-ReID and CUHK03.The experimental results were better than those of the comparative methods,which verifies the effectiveness of the proposed method.展开更多
Within the inventory era, urban shrinkage characterized by economic decline and space decay has been widely witnessed in China. The modes and trajectories of urban redevelopment have thus become areas of major concern...Within the inventory era, urban shrinkage characterized by economic decline and space decay has been widely witnessed in China. The modes and trajectories of urban redevelopment have thus become areas of major concern for both policymakers and scholars. Taking the multi-actor participation nature of redevelopment, this paper stemming from the game-theoretical approach demonstrates in empirical terms on two major fronts. First, the redevelopment of industrial land without the transfer of land use right is shown to be deadlocked by the incapacitation of the original land-user and unlocked with the participation of the new developer. Second, the preference of the original land-user to maximize its interests by operating by itself rather than continue to cooperate with the new developer is observed in the post-redevelopment stage. Therein, the entrepreneurial local government acts only as a “mediator” between the two market entities and tends not to directly intervene in their cooperation. Thus that, it is the reasonable distribution of potential benefits or the pricing of different rights in the land property right bundle rather than their definition that matters more for land redevelopment. Because the delineation of land property rights has never been a problem in a mature land market, particularly for stock industrial land.展开更多
Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and counterfeiting.Stamped seal inspection is commonly audited...Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and counterfeiting.Stamped seal inspection is commonly audited manually to ensure document authenticity.However,manual assessment of seal images is tedious and laborintensive due to human errors,inconsistent placement,and completeness of the seal.Traditional image recognition systems are inadequate enough to identify seal types accurately,necessitating a neural network-based method for seal image recognition.However,neural network-based classification algorithms,such as Residual Networks(ResNet)andVisualGeometryGroup with 16 layers(VGG16)yield suboptimal recognition rates on stamp datasets.Additionally,the fixed training data categories make handling new categories to be a challenging task.This paper proposes amulti-stage seal recognition algorithmbased on Siamese network to overcome these limitations.Firstly,the seal image is pre-processed by applying an image rotation correction module based on Histogram of Oriented Gradients(HOG).Secondly,the similarity between input seal image pairs is measured by utilizing a similarity comparison module based on the Siamese network.Finally,we compare the results with the pre-stored standard seal template images in the database to obtain the seal type.To evaluate the performance of the proposed method,we further create a new seal image dataset that contains two subsets with 210,000 valid labeled pairs in total.The proposed work has a practical significance in industries where automatic seal authentication is essential as in legal,financial,and governmental sectors,where automatic seal recognition can enhance document security and streamline validation processes.Furthermore,the experimental results show that the proposed multi-stage method for seal image recognition outperforms state-of-the-art methods on the two established datasets.展开更多
Microphone array-based sound source localization(SSL)is a challenging task in adverse acoustic scenarios.To address this,a novel SSL algorithm based on deep neural network(DNN)using steered response power-phase transf...Microphone array-based sound source localization(SSL)is a challenging task in adverse acoustic scenarios.To address this,a novel SSL algorithm based on deep neural network(DNN)using steered response power-phase transform(SRP-PHAT)spatial spectrum as input feature is presented in this paper.Since the SRP-PHAT spatial power spectrum contains spatial location information,it is adopted as the input feature for sound source localization.DNN is exploited to extract the efficient location information from SRP-PHAT spatial power spectrum due to its advantage on extracting high-level features.SRP-PHAT at each steering position within a frame is arranged into a vector,which is treated as DNN input.A DNN model which can map the SRP-PHAT spatial spectrum to the azimuth of sound source is learned from the training signals.The azimuth of sound source is estimated through trained DNN model from the testing signals.Experiment results demonstrate that the proposed algorithm significantly improves localization performance whether the training and testing condition setup are the same or not,and is more robust to noise and reverberation.展开更多
Background Several face detection and recogni tion methods have been proposed in the past decades that have excellent performance.The conventional face recognition pipeline comprises the following:(1)face detection,(2...Background Several face detection and recogni tion methods have been proposed in the past decades that have excellent performance.The conventional face recognition pipeline comprises the following:(1)face detection,(2)face alignment,(3)feature extraction,and(4)similarity,which are independent of each other.The separate facial analysis stages lead to redundant model calculations,and are difficult for use in end-to-end training.Methods In this paper,we propose a novel end-to-end trainable convolutional network framework for face detection and recognition,in which a geometric transformation matrix is directly learned to align the faces rather than predicting the facial landmarks.In the training stage,our single CNN model is supervised only by face bounding boxes and personal identities,which are publicly available from WIDER FACE and CASIA-WebFace datasets.Our model is tested on Face Detection Dataset and Benchmark(FDDB)and Labeled Face in the Wild(LFW)datasets.Results The results show 89.24%recall for face detection tasks and 98.63%accura cy for face recognition tasks.展开更多
To address the issue of deteriorated PCB image quality in the quality inspection process due to insufficient or uneven lighting, we proposed an image enhancement fusion algorithm based on different color spaces. First...To address the issue of deteriorated PCB image quality in the quality inspection process due to insufficient or uneven lighting, we proposed an image enhancement fusion algorithm based on different color spaces. Firstly, an improved MSRCR method was employed for brightness enhancement of the original image. Next, the color space of the original image was transformed from RGB to HSV, followed by processing the S-channel image using bilateral filtering and contrast stretching algorithms. The V-channel image was subjected to brightness enhancement using adaptive Gamma and CLAHE algorithms. Subsequently, the processed image was transformed back to the RGB color space from HSV. Finally, the images processed by the two algorithms were fused to create a new RGB image, and color restoration was performed on the fused image. Comparative experiments with other methods indicated that the contrast of the image was optimized, texture features were more abundantly preserved, brightness levels were significantly improved, and color distortion was prevented effectively, thus enhancing the quality of low-lit PCB images.展开更多
The eco-environment-oriented development (EOD) mode is an innovative projectorganization and implementation approach that integrates ecological governance, industrialoperations, and regional development. However, this...The eco-environment-oriented development (EOD) mode is an innovative projectorganization and implementation approach that integrates ecological governance, industrialoperations, and regional development. However, this mode still requires more in-depthresearch to strengthen its applicability to spatial perspectives and rural patterns. This studycontributes to this context by proposing a rural spatial governance framework based on theEOD mode, focusing on the three main governance elements: space, capital, and subject.By constructing a conceptual model of the multidimensional governance effectiveness ofEOD systems, it reveals the coupling mechanisms of three rural elements and proposes governance modes with spatially integrated optimization, capital value circulation, and rural subject connection as the focus of elemental regulation. This mode is further demonstratedthrough instantiation. In response to the developmental dilemmas of the villages’ overalldecline owing to coal mining subsidence on the Weibei Plateau, an integrated transformationplan for production, living, and ecological spaces is formulated, based on which the stagespecific focuses are clarified in the holistic governance path of “space-capital-subject”. Theresearch findings exemplify the application value and feasibility in regulating element relationships and balancing multiple benefits and can provide a reference at the spatial level topromote rural sustainable development through ecological governance.展开更多
Polycentric urban development has profound impacts on urban development worldwide.Most studies have identified its complex drivers of social economy and natural condition while ignoring the state-led policy factors.In...Polycentric urban development has profound impacts on urban development worldwide.Most studies have identified its complex drivers of social economy and natural condition while ignoring the state-led policy factors.In recent years,China has undergone dramatic administrative division adjustment(ADA)during the process of unique state-led urbanization.However,as a crucial government strategy,the impacts of ADA on urban polycentricity remain unclear.This research investigates the relationship between ADA and urban polycentricity through spatial difference-in-differences models.The results reveal that ADA has contributed to the polycentric urban development in China.Specifically,boundary restructuring has more substantial impacts than hierarchy reorganization.In addition,ADA has significantly promoted urban polycentricity in local cities in central China and neighbouring cities in eastern China,while it has no significant effects in western China.Furthermore,ADA reshapes urban polycentricity mainly by the influencing mechanism of construction land and industrial structure.Policymakers should consider the various ADA’s impacts on urban polycentricity with socio-economic conditions.This research provides a deeper insight into urban spatial transformation with state-led drivers.展开更多
According to the anti-phase sine current superposition theorem, the orientation, the magnetic flux density, the angular speed and the rotational direction of the spatial universal rotating magnetic field (SURMF) can...According to the anti-phase sine current superposition theorem, the orientation, the magnetic flux density, the angular speed and the rotational direction of the spatial universal rotating magnetic field (SURMF) can be controlled within the tri-axial orthogonal square Helmholtz coils (TOSHC). Nevertheless, three coupling direction angles of the normal vector of the SURMF in the Descartes coordinate system cannot be separately controlled, thus the adjustment of the orientation of the SURMF is difficult and the flexibility of the robotic posture control is restricted. For the dimension reduction and the decoupling of control variables, the orthogonal transformation operation theorem of the SURMF is proposed based on two independent rotation angular variables, which employs azimuth and altitude angles as two variables of the three-phase sine current superposition formula derived by the orthogonal rotation inverse transformation. Then the unique control rules of the orientation and the rotational direction of the SURMF are generalized in each spatial quadrant, thus the scanning of the normal vector of the SURMF along the horizontal or vertical direction can be achieved through changing only one variable, which simplifies the control process of the orientation of the SURMF greatly. To validate its feasibility and maneuverability, experiments were conducted in the animal intestine utilizing the innovative dual hemisphere capsule robot (DHCR) with active and passive modes. It was demonstrated that the posture adjustment and the steering rolling locomotion of the DHCR can be realized through single variable control, thus the orthogonal transformation operation theorem makes the control of the orientation of the SURMF convenient and flexible significantly. This breakthrough will lay a foundation for the human-machine interaction control of the SURMF.展开更多
Speech separation is an active research topic that plays an important role in numerous applications,such as speaker recognition,hearing pros-thesis,and autonomous robots.Many algorithms have been put forward to improv...Speech separation is an active research topic that plays an important role in numerous applications,such as speaker recognition,hearing pros-thesis,and autonomous robots.Many algorithms have been put forward to improve separation performance.However,speech separation in reverberant noisy environment is still a challenging task.To address this,a novel speech separation algorithm using gate recurrent unit(GRU)network based on microphone array has been proposed in this paper.The main aim of the proposed algorithm is to improve the separation performance and reduce the computational cost.The proposed algorithm extracts the sub-band steered response power-phase transform(SRP-PHAT)weighted by gammatone filter as the speech separation feature due to its discriminative and robust spatial position in formation.Since the GRU net work has the advantage of processing time series data with faster training speed and fewer training parameters,the GRU model is adopted to process the separation featuresof several sequential frames in the same sub-band to estimate the ideal Ratio Masking(IRM).The proposed algorithm decomposes the mixture signals into time-frequency(TF)units using gammatone filter bank in the frequency domain,and the target speech is reconstructed in the frequency domain by masking the mixture signal according to the estimated IRM.The operations of decomposing the mixture signal and reconstructing the target signal are completed in the frequency domain which can reduce the total computational cost.Experimental results demonstrate that the proposed algorithm realizes omnidirectional speech sep-aration in noisy and reverberant environments,provides good performance in terms of speech quality and intelligibility,and has the generalization capacity to reverberate.展开更多
Some results and developments on the extension of the inverse scattering transform to solve non-linear evolution equations in one time and two space dimensions are described.
Face reshaping aims to adjust the shape of a face in a portrait image to make the face aesthetically beautiful,which has many potential applications.Existing methods 1)operate on the pre-defined facial landmarks,leadi...Face reshaping aims to adjust the shape of a face in a portrait image to make the face aesthetically beautiful,which has many potential applications.Existing methods 1)operate on the pre-defined facial landmarks,leading to artifacts and distortions due to the limited number of landmarks,2)synthesize new faces based on segmentation masks or sketches,causing generated faces to look dissatisfied due to the losses of skin details and difficulties in dealing with hair and background blurring,and 3)project the positions of the deformed feature points from the 3D face model to the 2D image,making the results unrealistic because of the misalignment between feature points.In this paper,we propose a novel method named face shape transfer(FST)via semantic warping,which can transfer both the overall face and individual components(e.g.,eyes,nose,and mouth)of a reference image to the source image.To achieve controllability at the component level,we introduce five encoding networks,which are designed to learn feature embedding specific to different face components.To effectively exploit the features obtained from semantic parsing maps at different scales,we employ a straightforward method of directly connecting all layers within the global dense network.This direct connection facilitates maximum information flow between layers,efficiently utilizing diverse scale semantic parsing information.To avoid deformation artifacts,we introduce a spatial transformer network,allowing the network to handle different types of semantic warping effectively.To facilitate extensive evaluation,we construct a large-scale high-resolution face dataset,which contains 14,000 images with a resolution of 1024×1024.Superior performance of our method is demonstrated by qualitative and quantitative experiments on the benchmark dataset.展开更多
基金supported by the Research Center for Chengdu History and Chengdu Literature[CLWX24004]the Centre for Southeast Asia Economic and Culture Studies[DNY2415]the Sichuan Landscape and Recreation Research Center[JGYQ2025027].
文摘Chengdu teahouses,as core public spaces in marketplace society,have undergone transformative reconstruction-from“containers of everyday life”to“containers of commercial traffic and digital flows”-during the process of modernization.Employing spatial archaeology as a methodology,combined with fieldwork and analysis of historical documents,this study systematically examines the diachronic evolution of architectural forms,functional orientations,and social networks within Chengdu teahouses.The study reveals the logic of spatial reconstruction under the interplay of multiple forces,including cultural heritage preservation,capital-driven development,and technological intervention.The findings identify three paradigms of spatial transformation in teahouses.First,heritage specimenization,which reinforces the continuity of collective memory through symbolic extraction but risks diminishing the vitality of everyday social interactions.Second,consumption upgrading,which caters to the demands of emerging groups through iterative business models yet necessitates vigilance against spatial differentiation eroding marketplace inclusivity.Third,digital parasitism,which expands communicative dimensions through technological empowerment but confronts the risk of flattening localized knowledge.These paradigms reflect both adaptive responses of traditional spaces to contemporary pressure and the tension of reconstruction imposed by instrumental rationality on marketplace networks.The study demonstrates that spatial transformation in Chengdu teahouses is not unidirectional alienation but rather a multifaceted configuration where the continuity of tradition coexists with innovative practices amid functional diversification.This research advocates for striking a balance between the preservation of traditional spaces and modern renewal and explores organic integration approaches for traditional and modern elements,thereby providing a theoretical framework and practical insights for the transformation of traditional public spaces.
基金supported by the National Key Research and Development Program of China(No.2020YFB2010800)the National Natural Science Foundation of China(Nos.51875433 and 92060302)+1 种基金the Natural Science Foundation of Shaanxi Province,China(No.2019KJXX-043,2021JC-04)the Fundamental Research Funds for the Central Universities and the Foundation of Beilin District,China(No.GX2029)。
文摘Blade-health monitoring is intensely required for turbomachinery because of the high failure risk of rotating blades.Blade-Tip Timing(BTT)is considered as the most promising technique for operational blade-vibration monitoring,which obtains the parameters that characterize the blade condition from recorded signals.However,its application is hindered by severe undersampling and stringent probe layouts.An inappropriate probe layout can make most of the existing methods invalid or inaccurate.Additionally,a general conflict arises between the allowed and required layouts because of arrangement restrictions.For the sake of economy and safety,parameter identification based on fewer probes has been preferred by users.In this work,a spatial-transformation-based method for parameter identification is proposed based on a single-probe BTT measurement.To present the general Sampling-Aliasing Frequency(SAFE)map definition,the traditional time-frequency analysis methods are extended to a time-sampling frequency.Then,a SAFE map is projected onto a parameter space using spatial transformation to extract the slope and intercept parameters,which can be physically interpreted as an engine order and a natural frequency using coordinate transformation.Finally,the effectiveness and robustness of the proposed method are verified by simulations and experiments under uniformly and nonuniformly variable speed conditions.
文摘The spatial transformations can be observed at different religious-historic towns of India due to urbanization. Research is based upon fact that there is substantial change in the built environment because of spatial transformations at the religious-historic towns. The process of modernization in the functions and spatial layout is unavoidable at any historic town. The study attempts to focus on various urban historic conservation components, including the look of historic buildings, their earlier uses, and its immediate surroundings to improve the built environment of historic towns. A theoretical framework for the urban conservation of ancient towns is the main objective of study. How to modernize the historic conservation function while preserving the space’s texture and integrity. The research started with the investigation of the morphological growth of Mathura district, India through satellite images and in-depth study of the evolution process of street network in Vrindavan town, which is one of the main temple towns of Mathura district. There is a significant difference in the layout & architectural character of old part and the newly developed Vrindavan. Due to increased accessibility and movement, the spatial structure of traditional religious precincts, which were once local integration centres, has significantly changed. Increasing & changing mode of transportation and further increase in the religious tourism might be the cause or a big reason for the spatial transformations and correspondingly there is a challenge to conserve & preserve the religious precincts of historic towns. The study tries to analyze spatial transformations with the help of Historical GIS at different scales of urban form. Suggestive measures to conserve the environmental ambience of religious-historic towns are the outcome of the research.
基金the Foshan Science and technology Innovation Team Project(No.FS0AA-KJ919-4402-0060)the National Natural Science Foundation of China(No.62263018)。
文摘In view of the weak ability of the convolutional neural networks to explicitly learn spatial invariance and the probabilistic loss of discriminative features caused by occlusion and background interference in pedestrian re-identification tasks,a person re-identification method combining spatial feature learning and multi-granularity feature fusion was proposed.First,an attention spatial transformation network(A-STN)is proposed to learn spatial features and solve the problem of misalignment of pedestrian spatial features.Then the network was divided into a global branch,a local coarse-grained fusion branch,and a local fine-grained fusion branch to extract pedestrian global features,coarse-grained fusion features,and fine-grained fusion features,respectively.Among them,the global branch enriches the global features by fusing different pooling features.The local coarse-grained fusion branch uses an overlay pooling to enhance each local feature while learning the correlation relationship between multi-granularity features.The local fine-grained fusion branch uses a differential pooling to obtain the differential features that were fused with global features to learn the relationship between pedestrian local features and pedestrian global features.Finally,the proposed method was compared on three public datasets:Market1501,DukeMTMC-ReID and CUHK03.The experimental results were better than those of the comparative methods,which verifies the effectiveness of the proposed method.
基金National Natural Science Foundation of China (41971215, 41701193)Youth Innovation Promotion Association, Chinese Academy of Sciences (2022317)。
文摘Within the inventory era, urban shrinkage characterized by economic decline and space decay has been widely witnessed in China. The modes and trajectories of urban redevelopment have thus become areas of major concern for both policymakers and scholars. Taking the multi-actor participation nature of redevelopment, this paper stemming from the game-theoretical approach demonstrates in empirical terms on two major fronts. First, the redevelopment of industrial land without the transfer of land use right is shown to be deadlocked by the incapacitation of the original land-user and unlocked with the participation of the new developer. Second, the preference of the original land-user to maximize its interests by operating by itself rather than continue to cooperate with the new developer is observed in the post-redevelopment stage. Therein, the entrepreneurial local government acts only as a “mediator” between the two market entities and tends not to directly intervene in their cooperation. Thus that, it is the reasonable distribution of potential benefits or the pricing of different rights in the land property right bundle rather than their definition that matters more for land redevelopment. Because the delineation of land property rights has never been a problem in a mature land market, particularly for stock industrial land.
基金the National Natural Science Foundation of China(Grant No.62172132)Public Welfare Technology Research Project of Zhejiang Province(Grant No.LGF21F020014)the Opening Project of Key Laboratory of Public Security Information Application Based on Big-Data Architecture,Ministry of Public Security of Zhejiang Police College(Grant No.2021DSJSYS002).
文摘Seal authentication is an important task for verifying the authenticity of stamped seals used in various domains to protect legal documents from tampering and counterfeiting.Stamped seal inspection is commonly audited manually to ensure document authenticity.However,manual assessment of seal images is tedious and laborintensive due to human errors,inconsistent placement,and completeness of the seal.Traditional image recognition systems are inadequate enough to identify seal types accurately,necessitating a neural network-based method for seal image recognition.However,neural network-based classification algorithms,such as Residual Networks(ResNet)andVisualGeometryGroup with 16 layers(VGG16)yield suboptimal recognition rates on stamp datasets.Additionally,the fixed training data categories make handling new categories to be a challenging task.This paper proposes amulti-stage seal recognition algorithmbased on Siamese network to overcome these limitations.Firstly,the seal image is pre-processed by applying an image rotation correction module based on Histogram of Oriented Gradients(HOG).Secondly,the similarity between input seal image pairs is measured by utilizing a similarity comparison module based on the Siamese network.Finally,we compare the results with the pre-stored standard seal template images in the database to obtain the seal type.To evaluate the performance of the proposed method,we further create a new seal image dataset that contains two subsets with 210,000 valid labeled pairs in total.The proposed work has a practical significance in industries where automatic seal authentication is essential as in legal,financial,and governmental sectors,where automatic seal recognition can enhance document security and streamline validation processes.Furthermore,the experimental results show that the proposed multi-stage method for seal image recognition outperforms state-of-the-art methods on the two established datasets.
基金This work is supported by the National Nature Science Foundation of China(NSFC)under Grant No.61571106Jiangsu Natural Science Foundation under Grant No.BK20170757the Natural Science Foundation of the Jiangsu Higher Education Institutions of China under grant No.17KJD510002.
文摘Microphone array-based sound source localization(SSL)is a challenging task in adverse acoustic scenarios.To address this,a novel SSL algorithm based on deep neural network(DNN)using steered response power-phase transform(SRP-PHAT)spatial spectrum as input feature is presented in this paper.Since the SRP-PHAT spatial power spectrum contains spatial location information,it is adopted as the input feature for sound source localization.DNN is exploited to extract the efficient location information from SRP-PHAT spatial power spectrum due to its advantage on extracting high-level features.SRP-PHAT at each steering position within a frame is arranged into a vector,which is treated as DNN input.A DNN model which can map the SRP-PHAT spatial spectrum to the azimuth of sound source is learned from the training signals.The azimuth of sound source is estimated through trained DNN model from the testing signals.Experiment results demonstrate that the proposed algorithm significantly improves localization performance whether the training and testing condition setup are the same or not,and is more robust to noise and reverberation.
文摘Background Several face detection and recogni tion methods have been proposed in the past decades that have excellent performance.The conventional face recognition pipeline comprises the following:(1)face detection,(2)face alignment,(3)feature extraction,and(4)similarity,which are independent of each other.The separate facial analysis stages lead to redundant model calculations,and are difficult for use in end-to-end training.Methods In this paper,we propose a novel end-to-end trainable convolutional network framework for face detection and recognition,in which a geometric transformation matrix is directly learned to align the faces rather than predicting the facial landmarks.In the training stage,our single CNN model is supervised only by face bounding boxes and personal identities,which are publicly available from WIDER FACE and CASIA-WebFace datasets.Our model is tested on Face Detection Dataset and Benchmark(FDDB)and Labeled Face in the Wild(LFW)datasets.Results The results show 89.24%recall for face detection tasks and 98.63%accura cy for face recognition tasks.
文摘To address the issue of deteriorated PCB image quality in the quality inspection process due to insufficient or uneven lighting, we proposed an image enhancement fusion algorithm based on different color spaces. Firstly, an improved MSRCR method was employed for brightness enhancement of the original image. Next, the color space of the original image was transformed from RGB to HSV, followed by processing the S-channel image using bilateral filtering and contrast stretching algorithms. The V-channel image was subjected to brightness enhancement using adaptive Gamma and CLAHE algorithms. Subsequently, the processed image was transformed back to the RGB color space from HSV. Finally, the images processed by the two algorithms were fused to create a new RGB image, and color restoration was performed on the fused image. Comparative experiments with other methods indicated that the contrast of the image was optimized, texture features were more abundantly preserved, brightness levels were significantly improved, and color distortion was prevented effectively, thus enhancing the quality of low-lit PCB images.
基金supported by the Project of National Key Research and Development Program,China of the 14th Five-Year Plan(Grant No.2022YFC3802801)the Project of Shaanxi Provincial Education Department 2022 Key Research Program,China(Grant No.22JY031)the Excellent Doctoral Dissertation Cultivation Fund Project of Xi’an University of Architecture and Technology,China(Grant No.2021XYBPY009).
文摘The eco-environment-oriented development (EOD) mode is an innovative projectorganization and implementation approach that integrates ecological governance, industrialoperations, and regional development. However, this mode still requires more in-depthresearch to strengthen its applicability to spatial perspectives and rural patterns. This studycontributes to this context by proposing a rural spatial governance framework based on theEOD mode, focusing on the three main governance elements: space, capital, and subject.By constructing a conceptual model of the multidimensional governance effectiveness ofEOD systems, it reveals the coupling mechanisms of three rural elements and proposes governance modes with spatially integrated optimization, capital value circulation, and rural subject connection as the focus of elemental regulation. This mode is further demonstratedthrough instantiation. In response to the developmental dilemmas of the villages’ overalldecline owing to coal mining subsidence on the Weibei Plateau, an integrated transformationplan for production, living, and ecological spaces is formulated, based on which the stagespecific focuses are clarified in the holistic governance path of “space-capital-subject”. Theresearch findings exemplify the application value and feasibility in regulating element relationships and balancing multiple benefits and can provide a reference at the spatial level topromote rural sustainable development through ecological governance.
基金National Social Science Foundation of China,No.18ZDA040Humanities and Social Sciences Planning Project of the Ministry of Education in China,No.19YJA630079。
文摘Polycentric urban development has profound impacts on urban development worldwide.Most studies have identified its complex drivers of social economy and natural condition while ignoring the state-led policy factors.In recent years,China has undergone dramatic administrative division adjustment(ADA)during the process of unique state-led urbanization.However,as a crucial government strategy,the impacts of ADA on urban polycentricity remain unclear.This research investigates the relationship between ADA and urban polycentricity through spatial difference-in-differences models.The results reveal that ADA has contributed to the polycentric urban development in China.Specifically,boundary restructuring has more substantial impacts than hierarchy reorganization.In addition,ADA has significantly promoted urban polycentricity in local cities in central China and neighbouring cities in eastern China,while it has no significant effects in western China.Furthermore,ADA reshapes urban polycentricity mainly by the influencing mechanism of construction land and industrial structure.Policymakers should consider the various ADA’s impacts on urban polycentricity with socio-economic conditions.This research provides a deeper insight into urban spatial transformation with state-led drivers.
基金supported by the National Natural Science Foundation of China (Grant Nos. 51277018, 61175102, & 51475115)the Open Fund of the State Key Laboratory of Mechanical Transmissions (Grant No.SKLMT-KFKT-201509)
文摘According to the anti-phase sine current superposition theorem, the orientation, the magnetic flux density, the angular speed and the rotational direction of the spatial universal rotating magnetic field (SURMF) can be controlled within the tri-axial orthogonal square Helmholtz coils (TOSHC). Nevertheless, three coupling direction angles of the normal vector of the SURMF in the Descartes coordinate system cannot be separately controlled, thus the adjustment of the orientation of the SURMF is difficult and the flexibility of the robotic posture control is restricted. For the dimension reduction and the decoupling of control variables, the orthogonal transformation operation theorem of the SURMF is proposed based on two independent rotation angular variables, which employs azimuth and altitude angles as two variables of the three-phase sine current superposition formula derived by the orthogonal rotation inverse transformation. Then the unique control rules of the orientation and the rotational direction of the SURMF are generalized in each spatial quadrant, thus the scanning of the normal vector of the SURMF along the horizontal or vertical direction can be achieved through changing only one variable, which simplifies the control process of the orientation of the SURMF greatly. To validate its feasibility and maneuverability, experiments were conducted in the animal intestine utilizing the innovative dual hemisphere capsule robot (DHCR) with active and passive modes. It was demonstrated that the posture adjustment and the steering rolling locomotion of the DHCR can be realized through single variable control, thus the orthogonal transformation operation theorem makes the control of the orientation of the SURMF convenient and flexible significantly. This breakthrough will lay a foundation for the human-machine interaction control of the SURMF.
基金This work is supported by Nanjing Institute of Technology(NIT)fund for Research Startup Projects of Introduced talents under Grant No.YKJ202019Nature Sci-ence Research Project of Higher Education Institutions in Jiangsu Province under Grant No.21KJB510018+1 种基金National Nature Science Foundation of China(NSFC)under Grant No.62001215NIT fund for Doctoral Research Projects under Grant No.ZKJ2020003.
文摘Speech separation is an active research topic that plays an important role in numerous applications,such as speaker recognition,hearing pros-thesis,and autonomous robots.Many algorithms have been put forward to improve separation performance.However,speech separation in reverberant noisy environment is still a challenging task.To address this,a novel speech separation algorithm using gate recurrent unit(GRU)network based on microphone array has been proposed in this paper.The main aim of the proposed algorithm is to improve the separation performance and reduce the computational cost.The proposed algorithm extracts the sub-band steered response power-phase transform(SRP-PHAT)weighted by gammatone filter as the speech separation feature due to its discriminative and robust spatial position in formation.Since the GRU net work has the advantage of processing time series data with faster training speed and fewer training parameters,the GRU model is adopted to process the separation featuresof several sequential frames in the same sub-band to estimate the ideal Ratio Masking(IRM).The proposed algorithm decomposes the mixture signals into time-frequency(TF)units using gammatone filter bank in the frequency domain,and the target speech is reconstructed in the frequency domain by masking the mixture signal according to the estimated IRM.The operations of decomposing the mixture signal and reconstructing the target signal are completed in the frequency domain which can reduce the total computational cost.Experimental results demonstrate that the proposed algorithm realizes omnidirectional speech sep-aration in noisy and reverberant environments,provides good performance in terms of speech quality and intelligibility,and has the generalization capacity to reverberate.
文摘Some results and developments on the extension of the inverse scattering transform to solve non-linear evolution equations in one time and two space dimensions are described.
文摘Face reshaping aims to adjust the shape of a face in a portrait image to make the face aesthetically beautiful,which has many potential applications.Existing methods 1)operate on the pre-defined facial landmarks,leading to artifacts and distortions due to the limited number of landmarks,2)synthesize new faces based on segmentation masks or sketches,causing generated faces to look dissatisfied due to the losses of skin details and difficulties in dealing with hair and background blurring,and 3)project the positions of the deformed feature points from the 3D face model to the 2D image,making the results unrealistic because of the misalignment between feature points.In this paper,we propose a novel method named face shape transfer(FST)via semantic warping,which can transfer both the overall face and individual components(e.g.,eyes,nose,and mouth)of a reference image to the source image.To achieve controllability at the component level,we introduce five encoding networks,which are designed to learn feature embedding specific to different face components.To effectively exploit the features obtained from semantic parsing maps at different scales,we employ a straightforward method of directly connecting all layers within the global dense network.This direct connection facilitates maximum information flow between layers,efficiently utilizing diverse scale semantic parsing information.To avoid deformation artifacts,we introduce a spatial transformer network,allowing the network to handle different types of semantic warping effectively.To facilitate extensive evaluation,we construct a large-scale high-resolution face dataset,which contains 14,000 images with a resolution of 1024×1024.Superior performance of our method is demonstrated by qualitative and quantitative experiments on the benchmark dataset.
