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4th International Conference on Machine Learning and Computer Application, ICMLCA 2023

作者： Dong, Niuniu Liang, Yihui Zou, Kun Li, Wensheng Feng, Fujian School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China School of Computer Science Zhongshan Institute University of Electronic Science and Technology of China Zhongshan China Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang China

ISBN: (数字)9781510680265

ISBN: (纸本)9781510680258

Video matting aims at accurately separating foreground from videos. Recent video matting researches pursue to eliminate auxiliary inputs. However, due to the limited ability of extracting global correlation features, these methods suffer from performance degradation when dealing with complex scenes or natural background videos. To address this challenge, we propose a video matting method called Video Matting Based on Local-Global Features Fusion (VMBLGFF) which can extract both comprehensive global correlation features and local subtle features. VMBLGFF contains two closely connected networks: a transformer network that utilizes window and global attention mechanisms to obtain global correlation features within and cross windows, and a fusion network that integrates local subtle features into the global correlation features to supplement the local detail information which may be overlooked by the attention mechanisms. VMBLGFF alleviates the issue of limiting global correlation features and has been benchmarked on both synthetic and real datasets, and the results demonstrate that VMBLGFF improves the quality of video matting and exhibits good generalization performance. © 2024 SPIE.

关键词： Computer vision

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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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Geometric Numerical Integral Method in Compact Lie Group 6

Geometric Numerical Integral Method in Compact Lie Group

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6th IEEE International Conference on intelligent Computing and Signal Processing, ICSP 2021

作者： Liu, Chao Yang, Shengyi Guizhou Minzu University Key Laboratory of Pattern Recognition Intelligent System of Guizhou Province Gui Yang China

ISBN: (纸本)9780738143705

Three dimensions special orthogonal group SO (3) is widely used to describe the rotation kinematics of the rigid body without local coordinates, which can avoid rotation singularity and unwinding in traditional methods. Propagating the rotation kinematics in SO (3) with a specific geometric integration method is not only to obtained numerical results with improved qualitative behavior, but also provided more accurate long-time integration results. While many studies have focused on geometric integration algorithms to preserve the geometric structure, this work has the additional objective of studying result accuracy. Integral curves on SO (3) obtained using the third-order Crouch-Grossman Lie group method are compared with numerical results using the third-order RKMK algorithms, the exponential coordinates method, and the simple projection method. Results show that the use of the Crouch-Grossman Lie group method better preserves the geometric structure of SO (3) for the larger time steps considered. It is also found that the third-order Crouch-Grossman algorithm is more accurate than the RKMK except for the smallest time step used. © 2021 IEEE.

关键词： Geometry

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Topological phases in photonic microring lattices with projective symmetry

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Physical Review A 2024年第1期109卷 013516-013516页

作者： Yang Liu Chuang Jiang Wanting Wen Yiling Song Xiaohong Li Peixiang Lu Shaolin Ke Hubei Key Laboratory of Optical Information and Pattern Recognition Wuhan Institute of Technology Wuhan 430205 China Department of Physics Wenzhou University Zhejiang 325035 China Guangdong Intelligent Robotics Institute Dongguan 523808 China

Symmetry plays a key role in classifying topological phases, which can be enriched by the projective symmetry group in the presence of artificial gauge fields (AGFs). Here, we utilize two-dimensional (2D) photonic microring lattices to create three different topological states based on projective symmetry. By engineering link rings, we are able to flexibly manipulate the AGFs and coupling magnitude. As each plaquette carries a π flux, the two translation symmetries of a rectangle microring lattice are projectively represented. By applying different types of dimerization, we tune the spatial space to break translation symmetry and achieve a Möbius topological insulator with twisted edge bands and a graphenelike topological semimetal with flat bands, which we reflect by unique excitation spectra and field distributions. Additionally, by changing the configuration of gauge flux, the mirror and translation operators become anticommutative, leading to the fractal translation of the Brillouin zone. As a result, the band structure of topological edge modes experiences twice the period in momentum space. All results are confirmed by full-wave simulation. Our study has the potential to construct unprecedented photonic topological insulators benefiting from gauge fields.

关键词： Nanophotonics Photonics Topological effects in photonic systems Optical microcavities

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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 Institute 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 Institute 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 Institute 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

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Natural image matting based on image inpainting 2

Natural image matting based on image inpainting

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2nd International Conference on Computer Graphics, Image and Virtualization, ICCGIV 2022

作者： Zhang, Yuan Tan, Mian Zhou, Zhulian Yang, Yuan Liang, Yihui Feng, Fujian Guizhou Minzu University Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guiyang550025 China University of Electronic Science and Technology China School of Computer Science Zhongshan528400 China

ISBN: (纸本)9781665492508

Deep image matting is a hot problem with applications in computer vision and image processing. It has been widely used in image composition, film production and video editing etc. The current matting method based on image inpainting uses a deep neural network to inpaint the foreground target and background region to further improve the accuracy of alpha matte. However, when the trimap contains large unknown regions, the excessive inpainting of foreground and background produce a lot of redundant information, which leads to a degradation of alpha matte quality. Therefore, to address this issue, a natural image matting method based on image inpainting is designed. This method involves the refinement process for trimap, which improves the quality of the trimap, enlarges the foreground and background regions providing additional information for image matting. Extensive experimental results on the composition-1k dataset demonstrate that the presented method provide high-quality alpha mattes not only in the case that the trimap contains small unknown regions, but also in the case that the trimap contains large unknown regions. © 2022 IEEE.

关键词： Deep neural networks

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Research on Teaching Reform of 'Motor and Drive'Based on Matlab Simulation 2

Research on Teaching Reform of 'Motor and Drive'Based on Mat...

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2nd International Conference on Education, Knowledge and Information Management, ICEKIM 2021

作者： Chengwei, Zhang Yihua, Liang Liu, Chao Yang, Shengyi Key Laboratory of Pattern Recognition and Intelligent System of Guizhou Province Guizhou Minzu University Gui Yang China

ISBN: (纸本)9781728168340

'Motor and Drive' is a professional basic course with strong theory and wide application in practical engineering. Its theory is abstract and formula is complex, which is considered by teachers and automation students as one of the professional courses difficult to teach and learn. In order to better teaching and learning, teaching reform is provided. The teaching content is optimized, the teaching methods, experimental methods and assessment methods are reformed based on matlab simulation. It is helpful to improve the teaching quality, stimulate students' learning enthusiasm and solve practical problems. The teaching reform foundation of 'motor and drive' is provided in this paper. © 2021 IEEE.

关键词： Teaching

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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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Cross-Domain Person Re-identification Combining Feature Concatenation and Attention

Cross-Domain Person Re-identification Combining Feature Conc...

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作者： Feng Pan Lin Wang Yansha Zhang Jie Wang College of Data Science and Information Engineering Guizhou Minzu University Key Laboratory of Pattern Recognition and Intelligent System of Guizhou Province

To improve the insufficient generalization and poor cross-domain capability of the existing direct cross-dataset person re-identification methods,a cross-domain person re-identification method combining feature concatenation and attention(FCANet) is *** deep features of the network are concatenated to complement the feature information and obtain discriminatively feature,and the position attention module is introduced to enhance the data feature representation capability of the cross-domain task,using the joint training network of label smooth cross-entropy loss and triplet loss,model training in the source domain,and directly deploy to the target domain for *** verify the performance of the proposed method,it was experimented on three public datasets of Market1501,DukeMTMC-reID and MSMT17,which mAP and Rank1can reach 51.4%and 62.7% on *** results show that the proposed method has good performance in improving the generalization of cross-domain tasks,and the recognition accuracy outperforms the domain generalization algorithms of comparison.

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Building layover detection in SAR images via image translation 2

Building layover detection in SAR images via image translati...

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2nd International Conference on Signal Image Processing and Communication, ICSIPC 2022

作者： Wang, Haixia Yuan, Shuo Wang, Dongji Dong, Qiulei Hu, Zhanyi Key Laboratory for Robot and Intelligent Technology Shandong University of Science and Technology Shandong Province Qingdao City China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Haidian District Beijing China

ISBN: (纸本)9781510657694

Conventionally image translation is used to convert synthetic aperture radar (SAR) images to optical ones to increase interpretability. Due to the different imaging natures of SAR range sensing and optical directional projection, it is within the expectation that some kinds of SAR images could be reasonably translated into optical ones, while others not. Arguably, less good patches in the translated image could act as a potential indicator of salient differences of the two imaging mechanisms. Following this line of thought, considering in urban SAR images, the layover is mainly caused by buildings, we proposed a method to detect building layovers in SAR images by evaluating the correlation of the original SAR image and the translated one by the cycle-translation, that is, from SAR to optical to SAR translation. Because the presence of building is the main factor of the layover phenomenon in urban SAR images, building layover areas in SAR images are expected to be less correlated, or they should have a low correlation coefficient. Preliminary experiments validate our underlying principle and method. © 2022 SPIE.

关键词： Synthetic aperture radar

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