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检索条件"机构=Intelligent Robotics and Computer Vision Group/Department of Computer Science and Mathematics"
289 条 记 录,以下是221-230 订阅
排序:
Convolutional Neural Networks for Automatic Meter Reading
arXiv
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arXiv 2019年
作者: Laroca, Rayson Barroso, Victor Diniz, Matheus A. Gonçalves, Gabriel R. Schwartz, William Robson Menotti, David Federal University of Paraná Laboratory of Vision Robotics and Imaging Department of Informatics Av. Coronel Francisco Heráclito dos Santos 100 Curitiba81530-000 Brazil Federal University of Minas Gerais Smart Surveillance Interest Group Department of Computer Science Av. Antônio Carlos 6627 Belo Horizonte31270-010 Brazil
In this paper, we tackle Automatic Meter Reading (AMR) by leveraging the high capability of Convolutional Neural Networks (CNNs). We design a two-stage approach that employs the Fast-YOLO object detector for counter d... 详细信息
来源: 评论
Automatic classification of breast tissue according BIRADS categories using a clustering approach
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International Congress Series 2005年 1281卷 1399-1399页
作者: A. Oliver J. Martí J. Freixenet J. Pont R. Zwiggelaar Computer Vision and Robotics Group University of Girona Spain University Hospital Doctor Josep Trueta Girona Spain Department of Computer Science University of Aberystwyth UK
来源: 评论
Hydrone: Modeling of a Hybrid Unmanned Aerial Underwater Vehicle Considering Trans-Media Dynamics
SSRN
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SSRN 2024年
作者: de Oliveira Evald, Paulo Jefferson Dias Brião, Stephanie Loi Aoki, Vivian Misaki da Silva, César Bastos dos Santos Cardoso, Dayana Pinheiro, Pedro Miranda de Oliveira, Felipe Gomes André Barbosa Cunha, Mauro Jorge Drews, Paulo Lilles Intelligent Systems and Control Group Federal University of Pelotas RS Pelotas Brazil Intelligent Robotics and Automation Group Federal University of Rio Grande RS Rio Grande Brazil Department of Computer Engineering and Industrial Automation State University of Campinas SP Campinas Brazil Federal Institute of Education Science and Technology in Rio Grande do Sul RS Pelotas Brazil Institute of Exact Sciences and Technology Federal University of Amazonas Itacoatiara AM Amazonas Brazil Brazil
Research in mobile robotics is growing into applications for difficult-to-access environments, such as in rescue and transport missions. Furthermore, autonomous vehicles can perform data collection in complex approach... 详细信息
来源: 评论
CertainOdom: Uncertainty Weighted Multi-task Learning Model for LiDAR Odometry Estimation
CertainOdom: Uncertainty Weighted Multi-task Learning Model ...
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IEEE International Conference on robotics and Biomimetics
作者: Leyuan Sun Guanqun Ding Yusuke Yoshiyasu Fumio Kanehiro Department of Intelligent and Mechanical Interaction Systems Graduate School of Science and Technology University of Tsukuba Tsukuba Ibaraki Japan CNRS-AIST Joint Robotics Laboratory (JRL) IRL National Institute of Advanced Industrial Science and Technology (AIST). Digital Architecture Research Center (DARC) National Institute of Advanced Industrial Science and Technology (AIST) Tokyo Japan Computer Vision Research Team Artificial Intelligence Research Center (AIRC) National Institute of Advanced Industrial Science and Technology (AIST) Japan
As a basic and indispensable module, LiDAR odom-etry estimation is widely used in robotics. In recent years, learning-based modeling approaches for odometry estimation have been validated to be feasible. However, it i... 详细信息
来源: 评论
Learning offline: Memory replay in biological and artificial reinforcement learning
arXiv
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arXiv 2021年
作者: Roscow, Emma L. Chua, Raymond Costa, Rui Ponte Jones, Matt W. Lepora, Nathan Centre de Recerca Matemàtica Bellaterra Spain McGill University and Mila Montréal Canada Bristol Computational Neuroscience Unit Intelligent Systems Lab Department of Computer Science University of Bristol United Kingdom School of Physiology Pharmacology and Neuroscience University of Bristol Bristol United Kingdom Department of Engineering Mathematics Bristol Robotics Laboratory University of Bristol Bristol United Kingdom
Learning to act in an environment to maximise rewards is among the brain’s key functions. This process has often been conceptualised within the framework of reinforcement learning, which has also gained prominence in... 详细信息
来源: 评论
NTIRE 2023 Image Shadow Removal Challenge Report
NTIRE 2023 Image Shadow Removal Challenge Report
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2023 IEEE/CVF Conference on computer vision and Pattern Recognition Workshops, CVPRW 2023
作者: Vasluianu, Florin-Alexandru Seizinger, Tim Timofte, Radu Cui, Shuhao Huang, Junshi Tian, Shuman Fan, Mingyuan Zhang, Jiaqi Zhu, Li Wei, Xiaoming Wei, Xiaolin Luo, Ziwei Gustafsson, Fredrik K. Zhao, Zheng Sjölund, Jens Schön, Thomas B. Dong, Xiaoyi Zhang, Xi Sheryl Li, Chenghua Leng, Cong Yeo, Woon-Ha Oh, Wang-Taek Lee, Yeo-Reum Ryu, Han-Cheol Luo, Jinting Jiang, Chengzhi Han, Mingyan Wu, Qi Lin, Wenjie Yu, Lei Li, Xinpeng Jiang, Ting Fan, Haoqiang Liu, Shuaicheng Xu, Shuning Song, Binbin Chen, Xiangyu Zhang, Shile Zhou, Jiantao Zhang, Zhao Zhao, Suiyi Zheng, Huan Gao, Yangcheng Wei, Yanyan Wang, Bo Ren, Jiahuan Luo, Yan Kondo, Yuki Miyata, Riku Yasue, Fuma Naruki, Taito Ukita, Norimichi Chang, Hua-En Yang, Hao-Hsiang Chen, Yi-Chung Chiang, Yuan-Chun Huang, Zhi-Kai Chen, Wei-Ting Chen, I-Hsiang Hsieh, Chia-Hsuan Kuo, Sy-Yen Xianwei, Li Fu, Huiyuan Liu, Chunlin Ma, Huadong Fu, Binglan He, Huiming Wang, Mengjia She, Wenxuan Liu, Yu Nathan, Sabari Kansal, Priya Zhang, Zhongjian Yang, Huabin Wang, Yan Zhang, Yanru Phutke, Shruti S. Kulkarni, Ashutosh Khan, Md Raqib Murala, Subrahmanyam Vipparthi, Santosh Kumar Ye, Heng Liu, Zixi Yang, Xingyi Liu, Songhua Wu, Yinwei Jing, Yongcheng Yu, Qianhao Zheng, Naishan Huang, Jie Long, Yuhang Yao, Mingde Zhao, Feng Zhao, Bowen Ye, Nan Shen, Ning Cao, Yanpeng Xiong, Tong Xia, Weiran Li, Dingwen Xia, Shuchen Computer Vision Lab Ifi Caidas University of Würzburg Germany Computer Vision Lab Eth Zürich Switzerland Meituan Group China Department of Information Technology Uppsala University Sweden Institute of Automation Chinese Academy of Sciences Beijing China Nanjing China Maicro Nanjing China Department of Artificial Intelligence Convergence Sahmyook University Seoul Korea Republic of Megvii Technology China University of Electronic Science and Technology of China China University of Macau China China Toyota Technological Institute Japan Graduate Institute of Electronics Engineering National Taiwan University Taiwan Department of Electrical Engineering National Taiwan University Taiwan Graduate Institute of Communication Engineering National Taiwan University Taiwan ServiceNow United States Beijing University of Post and Teleconmunication Beijing China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education China Couger Inc. Computer Vision and Pattern Recognition Lab Indian Institute of Technology Ropar Punjab Rupnagar India Research Institute Singapore National University of Singapore Singapore Research Institute Singapore University of Sydney Australia Brain-Inspired Vision Laboratory Information Science and Technology Institution University of Science and Technology of China China State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou310027 China Key Laboratory of Advanced Manufacturing Technology of Zhejiang Province School of Mechanical Engineering Zhejiang University Hangzhou310027 China South China University of Technology China
This work reviews the results of the NTIRE 2023 Challenge on Image Shadow Removal. The described set of solutions were proposed for a novel dataset, which captures a wide range of object-light interactions. It consist... 详细信息
来源: 评论
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning
arXiv
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arXiv 2020年
作者: Li, Wenhao Jin, Bo Wang, Xiangfeng Yan, Junchi Zha, Hongyuan School of Data Science The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen518172 China School of Software Engineering Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai201804 China School of Computer Science and Technology Key Laboratory of Mathematics and Engineering Applications Ministry of Education East China Normal University Shanghai200062 China Department of Computer Science and Engineering Key Laboratory of Artificial Intelligence Ministry of Education Shanghai Jiao Tong University Shanghai200240 China
Traditional centralized multi-agent reinforcement learning (MARL) algorithms are sometimes unpractical in complicated applications due to non-interactivity between agents, the curse of dimensionality, and computation ... 详细信息
来源: 评论
Multi-view face detection based on real Adaboost algorithm
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Jisuanji Yanjiu yu Fazhan/computer Research and Development 2005年 第9期42卷 1612-1621页
作者: Wu, Bo Huang, Chang Ai, Haizhou Lao, Shihong State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing 100084 China Sensing Technology Laboratory Vision Sensing Technology Group Omron Corporation Kyoto 619-0283 Japan
In this paper, a multi-view face detection method based on real Adaboost algorithm is presented. Human faces are divided into several viewpoint categories according to their poses in 3D, and for each of these categori... 详细信息
来源: 评论
iCLAP: Shape recognition by combining proprioception and touch sensing
arXiv
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arXiv 2018年
作者: Luo, Shan Mou, Wenxuan Althoefer, Kaspar Liu, Hongbin Center for Robotics Research Department of Informatics King's College London LondonWC2R 2LS United Kingdom Department of Computer Science University of Liverpool LiverpoolL69 3BX United Kingdom Multimedia and Vision Research Group School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom School of Engineering and Materials Science Queen Mary University of London LondonE1 4NS United Kingdom
For humans, both the proprioception and touch sensing are highly utilized when performing haptic perception. However, most approaches in robotics use only either proprioceptive data or touch data in haptic object reco... 详细信息
来源: 评论
Regularization with multilevel non-stationary tight framelets for image restoration
arXiv
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arXiv 2021年
作者: Li, Yan-Ran Chan, Raymond H.F. Shen, Lixin Zhuang, Xiaosheng College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Guangdong Key Laboratory of Intelligent Information Processing Shenzhen Key Laboratory of Media Security Shenzhen University Shenzhen518060 China SZU Branch Shenzhen Institute of Artificial Intelligence and Robotics for Society China Department of Mathematics City University of Hong Kong Tat Chee Avenue Kowloon Tong Hong Kong Department of Mathematics Syracuse University SyracuseNY13244 United States
Variational regularization models are one of the popular and efficient approaches for image restoration. The regularization functional in the model carries prior knowledge about the image to be restored. The prior kno... 详细信息
来源: 评论