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A cross-domain person re-identification algorithm based on distribution-consistency and multi-label collaborative learning

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Multimedia Tools and Applications 2024年第38期83卷 85939-85962页

作者： Zhang, Baohua Hao, Chen Lv, Xiaoqi Gu, Yu Wang, Yueming Liu, Xin Ren, Yan Li, Jianjun School of Information Engineering Inner Mongolia University of Science and Technology Inner Mongolia Baotou014010 China School of Information Engineering Mongolia Industrial University Inner Mongolia Huhehaote010051 China Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing Inner Mongolia Baotou014010 China

To decrease domain shift in cross-domain person re-identification, existing methods generate pseudo labels for training models, however, the inherent distribution between source domain data and the hard quantization loss is ignored. Therefore, a cross-domain person re-identification method based on distribution consistency and multi-label collaborative learning is proposed. Firstly, a soft binary cross-entropy loss function is constructed to constrain the inter-sample relationship of cross-domain transformation, which can ensure the consistency of appearance features and sample distribution, and achieving feature cross-domain alignment. On this basis, in order to suppress the noise of hard pseudo labels, a multi-label collaborative learning network is constructed. The soft pseudo labels are generated by using the collaborative foreground features and global features to guide the network training, making the model adapt to the target domain. The experimental results show that the proposed method has better performance than that of recent representative methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Federated learning

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Dynamic Action recognition under Simulated Prosthetic Vision

Dynamic Action Recognition under Simulated Prosthetic Vision

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2020 International Conference on Networking and Network Applications, NaNA 2020

作者： Zhao, Ying Xu, Dantong Wang, Tie Ren, Yanchun Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Information Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia

ISBN: (纸本)9781728189543

Purpose. To assess the recognition pattern of dynamic action by visual prosthesis' wearers. Methods. Twenty volunteers (classified by gender and experience) were recruited to carried out action recognition test in simulated prosthetic vision. Twenty-three common dynamic actions video clips usually see in daily life were selected and formed the experimental action set which was divided into three parts including combined actions, simple actions and difficult actions in turn. The action animations made by 3D Studio Max were recorded by Banicam to convert to MP4 video format and processed to phosphene video clips by MATLAB in different resolutions (16 × 16, 24 × 24, 32 × 32, 48 × 48, 64 × 64, 128 × 128). Result. Comparing the recognition results, male group and female group had no significant difference. 48 × 48 resolution was the considerable latent capacity which subjects had stable performance. After a period of study, the performance of prosthesis wearers could be improved significantly. © 2020 IEEE.

关键词： MATLAB

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Research on the Detection of Abnormal Cervical Cells Based on Improved YOLOv7 9

Research on the Detection of Abnormal Cervical Cells Based o...

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9th International Conference on intelligent Computing and Signal processing, ICSP 2024

作者： Wang, Xuewei Yuan, Shuang Yang, Lidong Niu, Dawei Inner Mongolia University of Science and Technology School of Digtial and Intelligence Industry Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing Inner Mongolia China

ISBN: (纸本)9798350376548

Cervical cytologic screening is clinically important for the prevention and diagnosis of cervical cancer. Aiming at the many challenges in the detection of abnormal cervical cells, including the difficult detection of small targets of abnormal cervical cells, complex backgrounds, and uneven cell morphology, a detection algorithm for abnormal cervical cells based on improved YOLOv7 was proposed. The algorithm utilizes Deformable Convolutional Networks v2 (DCNv2) that adaptively de-tunes the scale and receptive field size to more effectively cope with the complexity and diversity of cervical cell images. The experimental results show that the improved YOLOv7 algorithm mAP achieves 57.26%, up to 73.88% accuracy, and 46.90% recall on the cervical abnormal cell dataset. Compared with the benchmark model, they increased by 4.07%, 3.39%, and 5.69%, respectively. © 2024 IEEE.

关键词： Convolution

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Adaptive Synchronization between Two Different Complex Networks with Time-Varying Delay Coupling

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中国物理快报（英文版） 2009年第6期26卷 59-62页

作者： CHEN Jian-Rui JIAO Li-Cheng WU Jian-She WANG Xiao-Hua Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligence Information ProcessingXidian UniversityXi'an 710071 College of Science Inner Mongolia University of TechnologyInner Mongolia 01 Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligence Information ProcessingXidian UniversityXi'an 710071

A new general network model for two complex networks with time-varying delay coupling is *** we investigate its synchronization *** two complex networks of the model differ in dynamic nodes,the number of nodes and the coupling *** using adaptive controllers,a synchronization criterion is *** examples are given to demonstrate the effectiveness of the obtained synchronization *** study may widen the application range of synchronization,such as in chaotic secure communication.

关键词： No English keywords

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Gait recognition Algorithm GCGait based on Skeleton 3

Gait Recognition Algorithm GCGait based on Skeleton

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3rd IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2023

作者： Ma, Ru Zhang, Jikai Jia, Mengyu Lv, Xiaoqi Inner Mongolia University of Science and Technology School of Information Engineering Baotou China Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing Baotou China Inner Mongolia University of Technology School of Information Engineering Hohhot China

ISBN: (纸本)9781665490788

To solve the problem of low accuracy of gait recognition in complex scenes, a novel skeleton-based gait recognition algorithm, GCGait, is proposed. Taking human posture as the input of gait feature, the interference caused by wearing changes and other factors is reduced. To extract sufficient input features, multi-branch input is used in the early stage of the model. By introducing the multi-attention mechanism, the network can learn the semantic information of the non-directly connected joints, excavate the most discriminative features from complex videos, and further improve the recognition performance. In order to reduce the influence of cross view, the fusion loss function is used in the experiment. Experimental results show that the average recognition rate of the proposed algorithm on the CASIA-B dataset is improved by 5.2%, and the average recognition accuracy on the OU-MVLP dataset is increased by 66.3%, which proves the effectiveness of the proposed method. © 2023 IEEE.

关键词： Complex networks

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Face Forgery Detection Algorithm Based on Improved MobileViT Network 8

Face Forgery Detection Algorithm Based on Improved MobileViT...

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8th International Conference on intelligent Computing and Signal processing, ICSP 2023

作者： Wang, Tiantian Lu, Xiaoqi Inner Mongolia University of Science and Technology School of Information Engineering Baotou014010 China Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing Baotou014010 China Inner Mongolia University of Technology Institute of Information Engineering Hohhot010051 China

ISBN: (纸本)9798350302455

DeepFakes blur the boundaries between reality and forgery, resulting in the collapse of exiting credit system, causing immeasurable consequences for national security and social order. Through analysis of existing face forgery techniques, it is found that most generation techniques rely on random noise distribution, and global information will be lost after up sampling. Therefore, we propose a deepfake detection algorithm based on improved MobileViT, which uses CNN local space biasing and the global space representation of the Transformer network to learn the local features and global representation of forged faces, respectively. Coordinate attention is introduced to obtain directional perception and position sensitive information, making the model locate synthetic traces of fake faces better and fusion local and global representation more effectively. For the improved generalization of the model, with the GELU activation function to solve the problem of neuron death. Our model achieved 96.2% on FF++(C23) datasets, and 93.7%,94.1%,96.3%,87.9% on DF, F2F, FS, and NT datasets, respectively. Comparing with previous methods, our model has shown detection robustness and better generalization. © 2023 IEEE.

关键词： National security

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Dynamic Action recognition Under Simulated Prosthetic Vision

Dynamic Action Recognition Under Simulated Prosthetic Vision

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International Conference on Networking and Network Applications (NaNA)

作者： Ying Zhao Dantong Xu Tie Wang Yanchun Ren Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing School of Information Engineering Inner Mongolia University of Science and Technology Baotou Inner Mongolia

ISBN: (数字)9781728189543

ISBN: (纸本)9781728189550

关键词： Three-dimensional displays Visual prosthesis Animation pattern recognition Matlab

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Research on the Detection of Abnormal Cervical Cells Based on Improved YOLOv7

Research on the Detection of Abnormal Cervical Cells Based o...

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6th International Conference on intelligent Computing and Signal processing (ICSP)

作者： Xuewei Wang Shuang Yuan Lidong Yang Dawei Niu Inner Mongolia Key Laboratory of Pattern Recognition and Intelligent Image Processing Inner Mongolia University of Science and Technology School of Digtial and Intelligence Industry Inner Mongolia China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

关键词： Accuracy Sensitivity Shape Prevention and mitigation Signal processing algorithms Signal processing Feature extraction Convolutional neural networks Detection algorithms Cervical cancer

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Controllability of neighborhood Corona product networks

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Science China(Information Sciences) 2024年第12期67卷 327-328页

作者： Bo LIU Xuan LI Qiang ZHANG Junjie HUANG Housheng SU Ministry of Education Key Laboratory for Intelligent Analysis and Security Governance of Ethnic Languages School of Information Engineering Minzu University of China School of Mathematical Sciences Inner Mongolia University Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology

Controlling networks aims to study the models, structures,and related dynamics of complex networks. The primary problem of controlling networks is to determine whether they are controllable. Nowadays, controllability has been widely studied and applied to system engineering and control theory, power systems, aerospace, and quantum systems. Various classical criteria include the Gram matrix criterion, Kalman rank criterion, and PBH test.

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Adaptive Synchronization between Two Different Complex Networks with Time-Varying Delay Coupling

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Chinese Physics Letters 2009年第6期26卷 61-64页

作者：陈建芮焦李成吴建设王晓华 Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligence Information Processing Xidian University Xi'an 710071 College of Science Inner Mongolia University of Technology Inner Mongolia 010051

A new general network model for two complex networks with time-varying delay coupling is presented. Then we investigate its synchronization phenomena. The two complex networks of the model differ in dynamic nodes, the number of nodes and the coupling connections. By using adaptive controllers, a synchronization criterion is derived. Numerical examples are given to demonstrate the effectiveness of the obtained synchronization criterion. This study may widen the application range of synchronization, such as in chaotic secure communication.

关键词： gamma-ray bursts gamma-rays relativity

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