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GAN-DIRNet:A Novel Deformable image Registration Approach for Multimodal Histological images

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Computers, Materials & Continua 2024年第7期80卷 487-506页

作者： Haiyue Li Jing Xie Jing Ke Ye Yuan Xiaoyong Pan Hongyi Xin Hongbin Shen inst.tute of image processing and pattern recognition Shanghai Jiao Tong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of ChinaShanghai200240China Department of Pathology Ruijin HospitalShanghai Jiao Tong UniversitySchool of MedicineShanghai200025China Department of Computer Science and Engineering Shanghai Jiao Tong UniversityShanghai200240China Global inst.tute of Future Technology Shanghai Jiao Tong UniversityShanghai200240China

Multi-modal histological image registration tasks pose significant challenges due to tissue staining operations causing partial loss and folding of *** neural network(CNN)and generative adversarial network(GAN)are pivotal inmedical image ***,existing methods often struggle with severe interference and deformation,as seen in histological images of conditions like Cushing’s *** argue that the failure of current approaches lies in underutilizing the feature extraction capability of the discriminator *** this study,we propose a novel multi-modal registration approach GAN-DIRNet based on GAN for deformable histological image *** begin with,the discriminators of two GANs are embedded as a new dual parallel feature extraction module into the unsupervised registration networks,characterized by implicitly extracting feature descriptors of specific ***,modal feature description layers and registration layers collaborate in unsupervised optimization,facilitating faster convergence and more precise ***,experiments and evaluations were conducted on the registration of the Mixed National inst.tute of Standards and Technology database(MNIST),eight publicly available datasets of histological sections and the Clustering-Registration-Classification-Segmentation(CRCS)dataset on the Cushing’s *** results demonstrate that our proposed GAN-DIRNet method surpasses existing approaches like DIRNet in terms of both registration accuracy and time efficiency,while also exhibiting robustness across different image types.

关键词： Histological images registration deformable registration generative adversarial network cushing’s disease machine learning computer vision

Graph convolutional network combined with random walks and graph attention network for node classification

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The Journal of China Universities of Posts and Telecommunications 2024年第3期31卷 1-14页

作者： Chen Yong Xie Xiaozhu Weng Wei College of Computer and Information Engineering Xiamen University of TechnologyXiamen 361024China Fujian Key Laboratory of pattern recognition and image Understanding Xiamen University of TechnologyXiamen 361024China

Graph conjoint attention(CAT)network is one of the best graph convolutional networks(GCNs)frameworks,which uses a weighting mechanism to identify important neighbor ***,this weighting mechanism is learned based on static information,which means it is susceptible to noisy nodes and edges,resulting in significant *** this paper,a method is proposed to obtain context dynamically based on random walk,which allows the context-based weighting mechanism to better avoid noise ***,the proposed context-based weighting mechanism is combined with the node content-based weighting mechanism of the graph attention(GAT)network to form a model based on a mixed weighting *** model is named as the context-based and content-based graph convolutional network(CCGCN).CCGCN can better discover important neighbors,eliminate noise edges,and learn node embedding by message *** show that CCGCN achieves state-of-the-art performance on node classification tasks in multiple datasets.

关键词： graph neural network(GNN) graph convolutional network(GCN) semi-supervised classification graph analysis

Learning group interaction for sports video understanding from a perspective of athlete

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Frontiers of Computer Science 2024年第4期18卷 175-188页

作者： Rui HE Zehua FU Qingjie LIU Yunhong WANG Xunxun CHEN Intelligent recognition and image processing(IRIP)Lab School of Computer Science and EngineeringBeihang UniversityBeijing 100191China Hangzhou Innovation inst.tute Behang UniversityHangzhou 310051China National Computer Network Emergency Response Technical Team/Coordination Center of China(CNCERT or CNCERT/CC) Beijing 100029China

Learning activities interactions between small groups is a key step in understanding team sports *** research focusing on team sports videos can be strictly regarded from the perspective of the audience rather than the *** team sports videos such as volleyball and basketball videos,there are plenty of intra-team and inter-team *** this paper,a new task named Group Scene Graph Generation is introduced to better understand intra-team relations and inter-team relations in sports *** tackle this problem,a novel Hierarchical Relation Network is *** all players in a video are finely divided into two teams,the feature of the two teams’activities and interactions will be enhanced by Graph Convolutional Networks,which are finally recognized to generate Group Scene *** evaluation,built on Volleyball dataset with additional 9660 team activity labels,a Volleyball+dataset is proposed.A baseline is set for better comparison and our experimental results demonstrate the effectiveness of our ***,the idea of our method can be directly utilized in another video-based task,Group Activity *** show the priority of our method and display the link between the two ***,from the athlete’s view,we elaborately present an interpretation that shows how to utilize Group Scene Graph to analyze teams’activities and provide professional gaming suggestions.

关键词： group scene graph group activity recognition scene graph generation graph convolutional network sports video understanding

Boosting Multi-modal Ocular recognition via Spatial Feature Reconstruction and Unsupervised image Quality Estimation

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Machine Intelligence Research 2024年第1期21卷 197-214页

作者： Zihui Yan Yunlong Wang Kunbo Zhang Zhenan Sun Lingxiao He Center for Research on Intelligent Perception and Computing National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China JD AI Research Beijing 100176China

In the daily application of an iris-recognition-at-a-distance(IAAD)system,many ocular images of low quality are *** the iris part of these images is often not qualified for the recognition requirements,the more accessible periocular regions are a good complement for *** further boost the performance of IAAD systems,a novel end-to-end framework for multi-modal ocular recognition is *** proposed framework mainly consists of iris/periocular feature extraction and matching,unsupervised iris quality assessment,and a score-level adaptive weighted fusion ***,ocular feature reconstruction(OFR)is proposed to sparsely reconstruct each probe image by high-quality gallery images based on proper feature ***,a brand new unsupervised iris quality assessment method based on random multiscale embedding robustness is *** from the existing iris quality assess-ment methods,the quality of an iris image is measured by its robustness in the embedding *** last,the fusion strategy exploits the iris quality score as the fusion weight to coalesce the complementary information from the iris and periocular *** experi-mental results on ocular datasets prove that the proposed method is obviously better than unimodal biometrics,and the fusion strategy can significantly improve therecognition performance.

关键词： Iris recognition periocular recognition spatial feature reconstruction fully convolutional network flexible matching unsupervised iris quality assessment adaptive weight fusion

Controllable transitions among phase-matching conditions in a single nonlinear crystal

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Chinese Optics Letters 2024年第2期22卷 141-147页

作者：曾梓琦尤世欣杨子祥袁晨智由成龙金锐博 Hubei Key Laboratory of Optical Information and pattern recognition Wuhan Institute of TechnologyWuhan 430205China Quantum Photonics Laboratory Department of Physics and AstronomyLouisiana State UniversityBaton RougeLouisiana 70803USA

Entangled photon pairs are crucial resources for quantum information processing *** the process of spontaneous parametric downconversion(SPDC),we can generate these photon pairs using bulk nonlinear ***,the crystal is designed to satisfy a specific type of phase-matching ***,we report controllable transitions among different types of phase matching in a single periodically poled potassium titanyl phosphate *** carefully selecting pump conditions,we can satisfy different phase-matching *** allows us to observe first-order Type-II,fifth-order Type-I,third-order Type-0,and fifth-order Type-II *** temperature-dependent spectra of our source were also analyzed in ***,we discussed the possibility of observing more than nine SPDCs in this *** work not only deepens the understanding of the physics behind phase-matching conditions,but also offers the potential for a highly versatile entangled biphoton source for quantum information research.

关键词： spontaneous parametric downconversion nonlinear crystals phase-matching condition

Revolutionary entrapment model of uniformly distributed swarm robots in morphogenetic formation

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Defence Technology（防务技术） 2024年第1期31卷 496-509页

作者： Chen Wang Zhaohui Shi Minqiang Gu Weicheng Luo Xiaomin Zhu Zhun Fan Shantou University ShantouGuangdongChina National University of Defense Technology ChangshaChina Key Lab of Digital Signal and image processing of Guangdong Province China

This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved *** the gene regulatory network method,the robots can generate entrapping patterns according to the environmental input,including the positions of the targets and ***,an adaptive decision mechanism is proposed,allowing each robot to choose the most well-adapted capture point on the pattern,based on its *** robots employ an improved Vicsek-model to maneuver to the planned capture point smoothly,without colliding with other robots or *** proposed decision mechanism,combined with the improved Vicsek-model,can form a uniform entrapment shape and create a revolving effect around targets while entrapping *** study also enables swarm robots,with an adaptive pattern formation,to entrap multiple targets in complex *** robots can be deployed in the military field of unmanned aerial vehicles’(UAVs)entrapping multiple *** experiments demonstrate the feasibility and superiority of the proposed gene regulatory network method.

关键词： Swarm intelligence Revolutionary entrapment Flocking Robots Gene regulatory network Vicsek-model Entrapping multiple targets

CASIA-Iris-Africa:A Large-scale African Iris image Database

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Machine Intelligence Research 2024年第2期21卷 383-399页

作者： Jawad Muhammad Yunlong Wang Junxing Hu Kunbo Zhang Zhenan Sun School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China

Iris biometrics is a phenotypic biometric trait that has proven to be agnostic to human natural physiological *** on iris biometrics has progressed tremendously,partly due to publicly available iris *** databases have been available to researchers that address pressing iris biometric challenges such as constraint,mobile,multispectral,synthetics,long-distance,contact lenses,liveness detection,***,these databases mostly contain subjects of Caucasian and Asian docents with very few *** many investigative studies on racial bias in face biometrics,very few studies on iris biometrics have been published,mainly due to the lack of racially diverse large-scale databases containing sufficient iris samples of Africans in the public ***,most of these databases contain a relatively small number of subjects and labelled *** paper proposes a large-scale African database named Chinese Academy of Sciences inst.tute of Automation(CASIA)-Iris-Africa that can be used as a complementary database for the iris recognition community to mediate the effect of racial biases on *** database contains 28717 images of 1023 African subjects(2046 iris classes)with age,gender,and ethnicity attributes that can be useful in demographically sensitive studies of *** of specific application protocols are incorporated with the database to ensure the database’s variability and *** results of some open-source state-of-the-art(SOTA)algorithms on the database are presented,which will serve as baseline *** relatively poor performances of the baseline algorithms on the proposed database despite better performance on other databases prove that racial biases exist in these iris recognition algorithms.

关键词： African iris recognition racial bias iris image database biometrics iris recognition

Comprehensive Relation Modelling for image Paragraph Generation

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Machine Intelligence Research 2024年第2期21卷 369-382页

作者： Xianglu Zhu Zhang Zhang Wei Wang Zilei Wang Automation Department University of Science and Technology of ChinaHefei 230027China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern RecognitionInstitute of AutomationChinese Academy of SciencesBeijing 100190China University of Chinese Academy of Sciences Beijing 100864China

image paragraph generation aims to generate a long description composed of multiple sentences,which is different from traditional image captioning containing only one *** of previous methods are dedicated to extracting rich features from image regions,and ignore modelling the visual *** this paper,we propose a novel method to generate a paragraph by modelling visual relationships ***,we parse an image into a scene graph,where each node represents a specific object and each edge denotes the relationship between two ***,we enrich the object features by implicitly encoding visual relationships through a graph convolutional network(GCN).We further explore high-order relations between different relation features using another graph convolutional *** addition,we obtain the linguistic features by projecting the predicted object labels and their relationships into a semantic embedding *** these features,we present an attention-based topic generation network to select relevant features and produce a set of topic vectors,which are then utilized to generate multiple *** evaluate the proposed method on the Stanford image-paragraph dataset which is currently the only available dataset for image paragraph generation,and our method achieves competitive performance in comparison with other state-of-the-art(SOTA)methods.

关键词： image paragraph generation visual relationship scene graph graph convolutional network(GCN) long short-term memory

New Method of Reconstruction from Nonparallel Stereo and Application to Surgical Navigator

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Journal of Shanghai Jiaotong university(Science) 2007年第6期12卷 707-712页

作者：王建华刘允才 inst. of image processing and pattern recognition Shanghai Jiaotong Univ.

A new method to reconstruct 3D scene points from nonparallel stereo is proposed. From a pair of conjugate images in an arbitrarily configured stereo system that has been calibrated, coordinates of 3D scene points can be computed directly using the method, bypassing the process of rectifying images or iterative solution involved in existing methods. Experiment results from both simulated data and real images validate the method. Practical application to surgical navigator shows that the method has advantages to improve efficiency and accuracy of 3D reconstruction from nonparallel stereo system in comparison with the conventional method that employs algorithm for standard parallel axes stereo geometry.

关键词： stereo nonparallel axes reconstruction method surgical navigator