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检索条件"机构=Institute for Pattern Recognition and Image Processing Computer Science Department"
294 条 记 录,以下是11-20 订阅
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SliceProp: A Slice-Wise Bidirectional Propagation Model for Interactive 3D Medical image Segmentation  1
SliceProp: A Slice-Wise Bidirectional Propagation Model for ...
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1st IEEE International Conference on Medical Artificial Intelligence, MedAI 2023
作者: Xu, Xin Lu, Wenjing Lei, Jiahao Qiu, Peng Shen, Hong-Bin Yang, Yang Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai200240 China Shanghai Ninth People's Hospital Shanghai Jiao Tong University School of Medicine Department of Vascular Surgery China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China
Interactive medical image segmentation methods have become increasingly popular in recent years. These methods combine manual labeling and automatic segmentation, reducing the workload of annotation while maintaining ... 详细信息
来源: 评论
Consistency-Guided Adaptive Alternating Training for Semi-Supervised Salient Object Detection
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IEEE Transactions on Circuits and Systems for Video Technology 2025年
作者: Chen, Liyuan Liu, Wei Wang, Hua Jeon, Sang-Woon Jiang, Yunliang Zheng, Zhonglong Zhejiang Normal University School of Computer Science and Technology Jinhua321004 China Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Department of Automation Shanghai200240 China Victoria University Institute for Sustainable Industries and Liveable Cities College of Engineering and Science MelbourneVIC8001 Australia Hanyang University Department of Electrical and Electronic Engineering Ansan Korea Republic of
This paper presents a novel approach that leverages two models to integrate features from numerous unlabeled images, addressing the challenge of semi-supervised salient object detection (SSOD). Unlike conventional met... 详细信息
来源: 评论
2M3DF: Advancing 3D Industrial Defect Detection with Multi Perspective Multimodal Fusion Network
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IEEE Transactions on Circuits and Systems for Video Technology 2025年
作者: Asad, Mujtaba Azeem, Waqar Jiang, He Mustafa, Hafiz Tayyab Yang, Jie Liu, Wei Shanghai Jiao Tong University Institute of Image Processing and Pattern Recognition Department of Automation Shanghai200240 China Lahore Garrison University Department of Software Engineering Lahore54000 Pakistan China University of Mining and Technology School of Information and Control Engineering Jiangsu Xuzhou221116 China Zhejiang Normal University School of Computer Science and Technology Jinhua321004 China
In the context of Industrial Anomaly Detection (IAD), ensuring the quality of manufactured products is critical. Traditional 2D based methods often fail to capture anomalies present in complex 3D shapes. For effective... 详细信息
来源: 评论
Noise Tolerance of Linear vs Non-Linear LiDAR Based Ego-Motion Drift Correction Methods
Noise Tolerance of Linear vs Non-Linear LiDAR Based Ego-Moti...
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IEEE International Conference on Intelligent computer Communication and processing (ICCP)
作者: Corvin-Petruț Cobârzan Cătălin-Cosmin Golban Sergiu Nedevschi Computer Science Department Technical University of Cluj-Napoca Romania Image Processing and Pattern Recognition Group Technical University of Cluj-Napoca Romania
We have previously proposed a linear approach for reducing the global drift of a video-based frame-to-frame trajectory estimation method by correcting it at selected points in time based on the alignment of past and c... 详细信息
来源: 评论
Generating Cartoon images from Face Photos with Cycle-Consistent Adversarial Networks
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computers, Materials & Continua 2021年 第11期69卷 2733-2747页
作者: Tao Zhang Zhanjie Zhang Wenjing Jia Xiangjian He Jie Yang School of Artificial Intelligence and Computer Science Jiangnan UniversityWuxi214000China Key Laboratory of Artificial Intelligence Jiangsu214000China The Global Big Data Technologies Centre University of Technology SydneyUltimoNSW2007Australia The Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong UniversityShanghai201100China
The generative adversarial network(GAN)is first proposed in 2014,and this kind of network model is machine learning systems that can learn to measure a given distribution of data,one of the most important applications... 详细信息
来源: 评论
Variational Feature Disentanglement for Few-Shot Domain Adaptation
Variational Feature Disentanglement for Few-Shot Domain Adap...
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IEEE International Conference on image processing
作者: Weiduo Wang Yun Gu Jie Yang Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China Institute of Medical Robotics Shanghai Jiao Tong University China Shanghai Center for Brain Science and Brain-Inspired Technology
In this paper, we focus on the few-shot domain adaptation problem. With limited training data in target domain, a new approach is emerging to acquire the transferable knowledge from the source domain. Previous methods...
来源: 评论
MBD-Net: Multi-Branch Dilated Convolutional Network With Cyst Discriminator for Renal Multi-Structure Segmentation
MBD-Net: Multi-Branch Dilated Convolutional Network With Cys...
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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
作者: Yusheng Liu Yingjie Zhao Meihuan Wang Yichao Hao Xiuying Wang Lisheng Wang Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China College of Medicine and Biological Information Engineering Northeastern University Shenyang China School of Computer Science The University of Sydney Sydney NSW Australia
In surgery-based renal cancer treatment, one of the most essential tasks is the three-dimensional (3D) kidney parsing on computed tomography angiography (CTA) images. In this paper, we propose an end-to-end convolutio...
来源: 评论
MobileUtr: Revisiting the relationship between light-weight CNN and Transformer for efficient medical image segmentation
arXiv
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arXiv 2023年
作者: Tang, Fenghe Nian, Bingkun Ding, Jianrui Quan, Quan Yang, Jie Liu, Wei Zhou, S. Kevin School of Biomedical Engineering Suzhou Institute for Advanced Research University of Science and Technology of China China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China School of Computer Science and Technology Harbin Institute of Technology China Institute of Computing Technology China
Due to the scarcity and specific imaging characteristics in medical images, light-weighting Vision Transformers (ViTs) for efficient medical image segmentation is a significant challenge, and current studies have not ... 详细信息
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RBP-Former: Joint Prediction of RNA-protein Binding Sites on Full-length RNA Transcripts for Multiple RBPs
RBP-Former: Joint Prediction of RNA-protein Binding Sites on...
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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)
作者: Yichong Li Xiaojian Liu Fan Cheng Xiaoyong Pan Yang Yang Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai China
RNA-binding proteins (RBPs) are essential for gene expression, and the complex RNA-protein interaction mechanisms require analysis of global RNA information. Therefore, accurate prediction of RBP binding sites on full... 详细信息
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Modeling Inter-Intra Heterogeneity for Graph Federated Learning
arXiv
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arXiv 2024年
作者: Yu, Wentao Chen, Shuo Tong, Yongxin Gu, Tianlong Gong, Chen School of Computer Science and Engineering Nanjing University of Science and Technology China Center for Advanced Intelligence Project RIKEN Japan State Key Laboratory of Complex & Critical Software Environment Beihang University China Jinan University China Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China
Heterogeneity is a fundamental and challenging issue in federated learning, especially for the graph data due to the complex relationships among the graph nodes. To deal with the heterogeneity, lots of existing method... 详细信息
来源: 评论