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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451-460 订阅
排序:
Unsupervised Multilayer Fuzzy Neural Networks for Image Clustering
SSRN
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SSRN 2022年
作者: Wang, Yifan Ishibuchi, Hisao Er, Meng Joo Zhu, Jihua School of Software Engineering Xi’an Jiaotong University Xi’an710049 China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Guangdong Provincial Key Laboratory of Brain-inspired Intelligent Computation China College of Marine Electrical Engineering Dalian Maritime University Dalian116026 China Institute of Artificial Intelligence Marine Robotics China
Nowadays, labeling a huge number of images is still a very challenging task. To tackle the problem of unlabeled data, unsupervised learning has been proposed. Among many unsupervised learning algorithms, K-means is th... 详细信息
来源: 评论
No One Left Behind: Real-World Federated Class-Incremental Learning
arXiv
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arXiv 2023年
作者: Dong, Jiahua Li, Hongliu Cong, Yang Sun, Gan Zhang, Yulun Van Gool, Luc The State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China The Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110169 China The University of Chinese Academy of Sciences Beijing100049 China The Department of Civil and Environmental Engineering Hong Kong Polytechnic University Hong Kong The College of Automation Science and Engineering South China University of Technology Guangzhou510640 China The Computer Vision Lab ETH Zürich Zürich8092 Switzerland
Federated learning (FL) is a hot collaborative training framework via aggregating model parameters of decentralized local clients. However, most FL methods unreasonably assume data categories of FL framework are known... 详细信息
来源: 评论
Neural Gradient Regularizer
arXiv
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arXiv 2023年
作者: Xu, Shuang Wang, Yifan Zhao, Zixiang Peng, Jiangjun Cao, Xiangyong Meng, Deyu Zhang, Yulun Timofte, Radu Van Gool, Luc School of Mathematics and Statistics Northwestern Polytechnical University Xi’an710021 China Research and Development Institute Northwestern Polytechnical University in Shenzhen Shenzhen518063 China School of Electronic and Information Engineering The Key Laboratory for Intelligent Networks and Network Security Ministry of Education Xi’an Jiaotong University Xi’an710049 China School of Mathematics and Statistics Xi’an Jiaotong University Xi’an710049 China Computer Vision Lab ETH Zurich Zürich8092 Switzerland
Owing to its significant success, the prior imposed on gradient maps has consistently been a subject of great interest in the field of image processing. Total variation (TV), one of the most representative regularizer... 详细信息
来源: 评论
HIPA: Hierarchical Patch Transformer for Single Image Super Resolution
arXiv
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arXiv 2022年
作者: Cai, Qing Qian, Yiming Li, Jinxing Lyu, Jun Yang, Yee-Hong Wu, Feng Zhang, David The Faculty of Information Science and Engineering Ocean University of China Shandong Qingdao266100 China The Department of Computer Science University of Manitoba WinnipegMBR3T 2N2 Canada The School of Computer Science and Technology Harbin Institute of Technology Guangdong Shenzhen518055 China The School of Nursing The Hong Kong Polytechnic University Hong Kong The Department of Computing Science University of Alberta EdmontonABT6G 2E9 Canada The School of Information Science and Technology University of Science and Technology of China Anhui Hefei230026 China The School of Data Science The Chinese University of Hong Kong Guangdong Shenzhen518172 China The Shenzhen Institute of Artificial Intelligence and Robotics for Society Guangdong Shenzhen518000 China Linklogis Joint Laboratory of Computer Vision and Artificial Intelligence Guangdong Shenzhen518172 China
Transformer-based architectures start to emerge in single image super resolution (SISR) and have achieved promising performance. However, most existing vision Transformer-based SISR methods still have two shortcomings... 详细信息
来源: 评论
Perceptive self-supervised learning network for noisy image watermark removal
arXiv
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arXiv 2024年
作者: Tian, Chunwei Zheng, Menghua Li, Bo Zhang, Yanning Zhang, Shichao Zhang, David School of Software Northwestern Polytechnical University Xi’an710129 China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology Xi’an710129 China School of Electronics and Information Northwestern Polytechnical University Xi’an710129 China School of Computer Science Northwestern Polytechnical University National Engineering Laboratory for Integrated AeroSpace-Ground-Ocean Big Data Application Technology Xi’an710129 China Guangxi Key Lab of Multisource Information Mining & Security College of Computer Science & Engineering Guangxi Normal University Guilin541004 China Shenzhen518172 China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518172 China
Popular methods usually use a degradation model in a supervised way to learn a watermark removal model. However, it is true that reference images are difficult to obtain in the real world, as well as collected images ... 详细信息
来源: 评论
Efficient Multi-Query Oriented Continuous Subgraph Matching
Efficient Multi-Query Oriented Continuous Subgraph Matching
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International Conference on Data Engineering
作者: Ziyi Ma Jianye Yang Xu Zhou Guoqing Xiao Jianhua Wang Liang Yang Kenli Li Xuemin Lin School of Artificial Intelligence Hebei University of Technology China Guangxi Key Laboratory of Machine Vision and Intelligent Control Wuzhou University China Cyberspace Institute of Advanced Technology Guangzhou University China Department of New Networks PengCheng Laboratory China College of Computer Science and Electronic Engineering Hunan University China Shenzhen Research Institute Hunan University China Antai College of Economics and Management Shanghai Jiao Tong University China
Continuous subgraph matching (CSM) is a critical task for analyzing dynamic graphs and has a wide range of applications, such as merchant fraud detection, cyber-attack hunting, and rumor detection. Although many effic... 详细信息
来源: 评论
Tactile-Based Object Pose Estimation Employing Extended Kalman Filter
Tactile-Based Object Pose Estimation Employing Extended Kalm...
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International Conference on Advanced robotics and Mechatronics (ICARM)
作者: Qiguang Lin Chaojie Yan Qiang Li Yonggen Ling Yu Zheng Wangwei Lee Zhaoliang Wan Bidan Huang Xiaofeng Liu Jiangsu Key laboratory of Special Robotic Technology College of IoT Engineering Hohai University Changzhou Jiangsu P.R. China State Key Laboratory of Industrial Control and Technology Zhejiang University Institute of Cyber-System and Control Hangzhou P.R. China Neuroinformatics Group Center for Cognitive Interaction Technology (CITEC) Bielefeld University Bielefeld Germany Tencent Robotics X Shenzhen China School of Computer Science and Engineering Sun Yat-sen University Guangzhou P.R.China
In this paper, we present a new approach to estimate the pose of an object being manipulated by a multi-fingered robotic hand. The method utilizes advanced tactile sensors with high spatial resolution to optimize the ...
来源: 评论
Long and Short-Term Constraints Driven Safe Reinforcement Learning for Autonomous Driving
arXiv
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arXiv 2024年
作者: Hu, Xuemin Chen, Pan Wen, Yijun Tang, Bo Chen, Long School of Artificial Intelligence Hubei University Wuhan430062 China Key Laboratory of Intelligent Sensing System and Security Hubei University Ministry of Education Hubei Wuhan430062 China Department of Electrical and Computer Engineering Worcester Polytechnic Institute WorcesterMA01609 United States State Key Laboratory of Multimodal Artificial Intelligence Systems State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing100190 China WAYTOUS Inc. Beijing100083 China Shenzhen518107 China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi’an710049 China
Reinforcement learning (RL) has been widely used in decision-making and control tasks, but the risk is very high for the agent in the training process due to the requirements of interaction with the environment, which... 详细信息
来源: 评论
V2-SfMLearner: Learning Monocular Depth and Ego-motion for Multimodal Wireless Capsule Endoscopy
arXiv
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arXiv 2024年
作者: Bai, Long Cui, Beilei Wang, Liangyu Li, Yanheng Yao, Shilong Yuan, Sishen Wu, Yanan Zhang, Yang Meng, Max Q.-H. Li, Zhen Ding, Weiping Ren, Hongliang Dept. of Electronic Engineering The Chinese University of Hong Kong Hong Kong City University of Hong Kong Hong Kong Shenzhen Key Laboratory of Robotics Perception and Intelligence Dept. of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen China The School of Mechanical Engineering Hubei University of Technology Wuhan China The Dept. of Gastroenterology Qilu Hospital of Shandong University Jinan China The School of Artificial Intelligence and Computer Science Nantong University Nantong China
Deep learning can predict depth maps and capsule ego-motion from capsule endoscopy videos, aiding in 3D scene reconstruction and lesion localization. However, the collisions of the capsule endoscopies within the gastr... 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