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检索条件"机构=Shenzhen Key Laboratory of Robotics and Computer Vision"
493 条 记 录,以下是291-300 订阅
排序:
InOR-Net: Incremental 3D Object Recognition Network for Point Cloud Representation
arXiv
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arXiv 2023年
作者: Dong, Jiahua Cong, Yang Sun, Gan Wang, Lixu Lyu, Lingjuan Li, Jun Konukoglu, Ender The State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China The University of Chinese Academy of Sciences Beijing100049 China The Computer Science Department Northwestern University Evanston United States The Sony AI Tokyo108-0075 Japan The School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China The Computer Vision Lab ETH Zurich Zürich8092 Switzerland
3D object recognition has successfully become an appealing research topic in the real-world. However, most existing recognition models unreasonably assume that the categories of 3D objects cannot change over time in t... 详细信息
来源: 评论
A Prediction Approach Based on Long Short-Term Memory Networks for Dynamic Multiobjective Optimization
SSRN
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SSRN 2024年
作者: Xu, Biao Rang, Gejie Li, Wenji Gong, Dunwei Fan, Zhun Yang, Shengxiang He, Jie College of Engineering Shantou University Shantou515063 China College of Automation and Electronic Engineering Qingdao University of Science and Technology Qingdao266100 China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou543002 China Shenzhen institute for Advanced Study UESTC Shenzhen518110 China School of Computer Science and Informatics De Montfort University LeicesterLE1 9BH United Kingdom Minjiang University China
Dynamic multiobjective optimization problems (DMOPs) present significant challenges to conventional evolutionary optimization methods because of the continuous changes in their Pareto-optimal sets (PSs) and fronts (PF... 详细信息
来源: 评论
Manifold-preserved GANs
arXiv
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arXiv 2021年
作者: Liu, Haozhe Liang, Hanbang Hou, Xianxu Wu, Haoqian Liu, Feng Shen, Linlin College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China
Generative Adversarial Networks (GANs) have been widely adopted in various fields. However, existing GANs generally are not able to preserve the manifold of data space, mainly due to the simple representation of discr... 详细信息
来源: 评论
Fingerprint Presentation Attack Detection by Channel-wise Feature Denoising
arXiv
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arXiv 2021年
作者: Liu, Feng Kong, Zhe Liu, Haozhe Zhang, Wentian Shen, Linlin The College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen University Shenzhen518060 China
Due to the diversity of attack materials, fingerprint recognition systems (AFRSs) are vulnerable to malicious attacks. It is thus important to propose effective fingerprint presentation attack detection (PAD) methods ... 详细信息
来源: 评论
Bioinspired Musculoskeletal Model-based Soft Wrist Exoskeleton for Stroke Rehabilitation
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Journal of Bionic Engineering 2020年 第6期17卷 1163-1174页
作者: Ning Li Tie Yang Yang Yang Peng Yu Xiujuan Xue Xingang Zhao Guoli Song Imad HElhajj Wenxue Wang Ning Xi Lianqing Liu State Key Laboratory of Robotics Shenyang Institute of AutomationChinese Academy of SciencesShenyang 110016China Institutes for Robotics and Itelligent Manufacturing Chinese Academy of SciencesShenyang 110169China University of Chinese Academy of Sciences Bejing 100049China Rehabilitation Center for the Disabled Shenyang 110015China Vision and Robotics Lab Department of Electrical and Computer EngineeringAmerican University of BeirutBeirut 11072020Lebanon Emerging Technologies Instinute Department of Industrial&Manufacturing Systems EngineeringUniversity of Hong KongPokfulamHong Kong 999077China
Exoskeleton robots have demonstrated the potential to rehabilitate stroke ***,poor human-machine physiological coupling causes unexpected damage to human of muscles and ***,inferior humanoid kinematics control would r... 详细信息
来源: 评论
Deep Learning Methods for Ship Classification: From Visible to Infrared Images
Deep Learning Methods for Ship Classification: From Visible ...
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robotics, Intelligent Control and Artificial Intelligence (RICAI), International Conference on
作者: Tianci Liu Hengjia Qin Zhuo Zhan Yunpeng Liu Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China Key Laboratory of Opto-Electronic Information Processing Chinese Academy of Sciences Shenyang China Key Laboratory of Image Understanding and Computer Vision Shenyang Liaoning Province China The Third Military Representative Office of the Air Force Equipment Department in Shenyang Region Shenyang Liaoning Province China
Deep learning methods have achieved excellent performances on visual tasks of target recognition and classification. The rapid development of autonomous seafaring vessels comes up with the requirement to recognize oth...
来源: 评论
PIPAL: A Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration  16th
PIPAL: A Large-Scale Image Quality Assessment Dataset for Pe...
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16th European Conference on computer vision, ECCV 2020
作者: Jinjin, Gu Haoming, Cai Haoyu, Chen Xiaoxing, Ye Ren, Jimmy S. Chao, Dong The School of Data Science The Chinese University of Hong Kong Shenzhen China ShenZhen Key Lab of Computer Vision and Pattern Recognition SIAT-SenseTime Joint Lab Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China SenseTime Research Science Park Hong Kong SIAT Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen China
Image quality assessment (IQA) is the key factor for the fast development of image restoration (IR) algorithms. The most recent IR methods based on Generative Adversarial Networks (GANs) have achieved significant impr... 详细信息
来源: 评论
Maximal η-clique maintenance over uncertain graph streams
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Information Sciences 2025年 717卷
作者: Ma, Ziyi Wang, Liqing Yang, Jianye Zhou, Xu Li, Kenli Gao, Cuiyun School of Artificial Intelligence Hebei University of Technology Tianjin300401 China Chinacoal Beijing Coal Mining Machinery Co. Ltd. Beijing102400 China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University Wuzhou543002 China Department of New Networks PengCheng Laboratory Shenzhen518055 China Cyberspace Institute of Advanced Technology Guangzhou University Guangzhou510006 China College of Computer Science and Electronic Engineering Hunan University Changsha410082 China Shenzhen518055 China
Maximal clique enumeration is a critical task for analyzing graph data and has a wide range of applications, such as community detection, protein complex identification, and group recommendation. Although many efficie... 详细信息
来源: 评论
UniFormer: Unifying Convolution and Self-attention for Visual Recognition
arXiv
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arXiv 2022年
作者: Li, Kunchang Wang, Yali Zhang, Junhao Gao, Peng Song, Guanglu Liu, Yu Li, Hongsheng Qiao, Yu ShenZhen Key Lab of Computer Vision and Pattern Recognition Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China University of Chinese Academy of Sciences Beijing100049 China Shanghai Artificial Intelligence Laboratory Shanghai200232 China National University of Singapore Singapore Shanghai Artificial Intelligence Laboratory China SenseTime Research China The Chinese University of Hong Kong Hong Kong
It is a challenging task to learn discriminative representation from images and videos, due to large local redundancy and complex global dependency in these visual data. Convolution neural networks (CNNs) and vision t... 详细信息
来源: 评论
Deep Learning Enables Large Depth-of-Field Images for Sub-Diffraction-Limit Scanning Superlens Microscopy
arXiv
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arXiv 2023年
作者: Sun, Hui Luo, Hao Wang, Feifei Chen, Qingjiu Chen, Meng Wang, Xiaoduo Yu, Haibo Zhang, Guanglie Liu, Lianqing Wang, Jianping Wu, Dapeng Li, Wen Jung Department of Mechanical Engineering City University of Hong Kong Hong Kong State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China Department of Electrical and Electronics Engineering The University of Hong Kong Hong Kong Shenzhen518000 China Department of Computer Science City University of Hong Kong Hong Kong
Scanning electron microscopy (SEM) is indispensable in diverse applications ranging from microelectronics to food processing because it provides large depth-of-field images with a resolution beyond the optical diffrac... 详细信息
来源: 评论