咨询与建议

限定检索结果

文献类型

  • 154 篇 期刊文献
  • 135 篇 会议
  • 4 册 图书

馆藏范围

  • 293 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 182 篇 工学
    • 118 篇 计算机科学与技术...
    • 103 篇 软件工程
    • 56 篇 控制科学与工程
    • 47 篇 光学工程
    • 43 篇 生物工程
    • 40 篇 信息与通信工程
    • 33 篇 生物医学工程(可授...
    • 20 篇 电气工程
    • 16 篇 电子科学与技术(可...
    • 13 篇 机械工程
    • 13 篇 仪器科学与技术
    • 12 篇 动力工程及工程热...
    • 12 篇 交通运输工程
    • 8 篇 力学(可授工学、理...
    • 8 篇 化学工程与技术
    • 7 篇 土木工程
    • 7 篇 安全科学与工程
  • 117 篇 理学
    • 48 篇 生物学
    • 47 篇 数学
    • 42 篇 物理学
    • 16 篇 统计学(可授理学、...
    • 8 篇 化学
  • 37 篇 管理学
    • 21 篇 图书情报与档案管...
    • 18 篇 管理科学与工程(可...
    • 10 篇 工商管理
  • 24 篇 医学
    • 23 篇 临床医学
    • 22 篇 基础医学(可授医学...
    • 14 篇 药学(可授医学、理...
    • 7 篇 公共卫生与预防医...
  • 8 篇 农学
  • 7 篇 法学
    • 7 篇 社会学
  • 3 篇 经济学
  • 2 篇 教育学
  • 1 篇 文学
  • 1 篇 军事学
  • 1 篇 艺术学

主题

  • 15 篇 cameras
  • 15 篇 intelligent robo...
  • 12 篇 robot sensing sy...
  • 12 篇 feature extracti...
  • 12 篇 computer vision
  • 11 篇 trajectory
  • 11 篇 robot vision sys...
  • 10 篇 computer science
  • 10 篇 image segmentati...
  • 9 篇 mobile robots
  • 8 篇 pixel
  • 8 篇 image edge detec...
  • 8 篇 robustness
  • 7 篇 object detection
  • 7 篇 artificial intel...
  • 7 篇 robot kinematics
  • 7 篇 training
  • 6 篇 deep learning
  • 6 篇 robots
  • 6 篇 system-on-chip

机构

  • 14 篇 embedded vision ...
  • 7 篇 embedded vision ...
  • 7 篇 intelligent robo...
  • 7 篇 heidelberg
  • 6 篇 centre for medic...
  • 6 篇 department of co...
  • 6 篇 faculty of mathe...
  • 5 篇 department of qu...
  • 5 篇 computer vision ...
  • 5 篇 ihu strasbourg s...
  • 5 篇 shenzhen institu...
  • 5 篇 university of ch...
  • 5 篇 ural federal uni...
  • 4 篇 computer vision ...
  • 4 篇 heidelberg divis...
  • 4 篇 department of co...
  • 4 篇 intelligent robo...
  • 4 篇 heidelberg divis...
  • 4 篇 centre for intel...
  • 4 篇 fraunhofer mevis...

作者

  • 24 篇 kryjak tomasz
  • 9 篇 puig domenec
  • 7 篇 bakas spyridon
  • 7 篇 szolc hubert
  • 7 篇 domenec puig
  • 6 篇 reinke annika
  • 6 篇 ma jun
  • 6 篇 shen linlin
  • 6 篇 menze bjoern
  • 6 篇 blachut krzyszto...
  • 6 篇 vladimir popov
  • 6 篇 maier-hein lena
  • 6 篇 m.a. garcia
  • 5 篇 godau patrick
  • 5 篇 abdellah chehri
  • 5 篇 reyes mauricio
  • 5 篇 kofler florian
  • 5 篇 kyrki ville
  • 5 篇 eisenmann matthi...
  • 5 篇 garcia miguel an...

语言

  • 282 篇 英文
  • 10 篇 其他
  • 1 篇 中文
检索条件"机构=Intelligent Robotics and Computer Vision Group/Department of Computer Science and Mathematics"
293 条 记 录,以下是231-240 订阅
排序:
Opportunities and challenges for monitoring terrestrial biodiversity in the robotics age
收藏 引用
Nature Ecology & Evolution 2025年 1-12页
作者: Stephen Pringle Jessica C. Fisher Gail E. Austen Jake E. Bicknell Nicolas J. Deere Mohammad S. Farhadinia Charlie J. Gardner Richard A. Griffiths Daniel J. Ingram Matthew J. Struebig Natalie Yoh Zoe G. Davies Martin Dallimer Mark A. Goddard Katherine C. R. Baldock Miranda T. Prendergast-Miller Léni K. Le Goff Emma Hart Simón C. Smith Simon J. Langdale Sara-Adela Abad Marc Ancrenaz Fabio Angeoletto Fernando Auat Cheein Joseph J. Bailey Lindsay F. Banin Cristina Banks-Leite Aliyu S. Barau Reshu Bashyal Adam J. Bates Jon Bielby Serge Wich Christopher D. Williams Petra Bosilj Marc Hanheide Emma R. Bush Simon J. Butler Dan Carpenter Christopher F. Clements Antoine Cully Kendi F. Davies Brett A. Melbourne Michael Dodd Rosie Drinkwater Don A. Driscoll Guillaume Dutilleux Mads Dyrmann David P. Edwards Aisyah Faruk Richard Field Franziska Schrodt Robert J. Fletcher Chris W. Foster Richard Fox Richard M. Francksen Aldina M. A. Franco Alison M. Gainsbury Ioanna Giorgi Giovanni L. Masala Salua Hamaza Matt W. Hayward Marcus Hedblom Thorunn Helgason Sui P. Heon Kevin A. Hughes Edmund R. Hunt George Jackson-Mills Kelly Jowett Timothy H. Keitt Laura N. Kloepper Stephanie Kramer-Schadt Jim Labisko Frédéric Labrosse Jenna Lawson Nicolas Lecomte Ricardo F. de Lima Nick A. Littlewood Harry H. Marshall Lindsay C. Maskell Eleni Matechou Barbara Mazzolai Alistair McConnell Aslan Miriyev Eric Djomo Nana Alessandro Ossola Sarah Papworth Catherine L. Parr Ana Payo-Payo Gad Perry Nathalie Pettorelli Marcus Rowcliffe Rajeev Pillay Simon G. Potts Lan Qie Carl D. Soulsbury Persie Rolley-Parnell Stephen J. Rossiter Heather Rumble Jon P. Sadler Christopher J. Sandom Asiem Sanyal Sarab S. Sethi Adi Shabrani Robert Siddall Robbert P. H. Snep Margaret C. Stanley Philip A. Stephens P. J. Stephenson Matthew Studley Martin Svátek Gilbert Tang Nicholas K. Taylor Kate D. L. Umbers Robert J. Ward Patrick J. C. White Mark J. Whittingham Ibrahim B. Yakubu Syed A. R. Zaidi Anna Zmarz Joeri A. Zwerts Durrell Institute of Conservation and Ecology (DICE) School of Natural Sciences University of Kent Canterbury UK Centre for Environmental Policy Imperial College London London UK Department of Geography and Environmental Sciences Northumbria University Newcastle upon Tyne UK School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh UK Synthotech Ltd Milner Court Hornbeam Square Harrogate UK Mechanical Engineering Department University College London London UK HUTAN SWD Kota Kinabalu Malaysia Programa de Pós-Graduação em Gestão e Tecnologia Ambiental da Universidade Federal de Rondonópolis Rondonópolis Brasil Department of Engineering Harper Adams University Newport UK Applied Ecology Research Group School of Life Sciences Anglia Ruskin University Cambridge UK Centre for Ecology and Hydrology Penicuik UK Department of Life Sciences Imperial College London Silwood Park Campus Ascot UK Department of Urban and Regional Planning Faculty of Earth and Environmental Sciences Bayero University Kano Nigeria Greenhood Nepal Kathmandu Nepal Animal Rural & Environmental Sciences Nottingham Trent University Nottinghamshire UK School of Biological and Environmental Sciences Liverpool John Moores University Liverpool UK Lincoln Centre for Autonomous Systems University of Lincoln Lincoln UK Royal Botanic Garden Edinburgh Edinburgh UK School of Biological Sciences University of East Anglia Norwich Research Park Norwich UK Digital Ecology Limited Bristol UK School of Biological Sciences University of Bristol Bristol UK Department of Computing Imperial College London London UK Department of Ecology and Evolutionary Biology University of Colorado Boulder CO USA Faculty of Science Technology Engineering and Mathematics (STEM) The Open University Walton Hall Milton Keynes UK Palaeogenomics Group Faculty of Veterinary Medicine Ludwig Maximilian University Munich Munich Germany School of Life and Environmental Sciences
With biodiversity loss escalating globally, a step change is needed in our capacity to accurately monitor species populations across ecosystems. Robotic and autonomous systems (RAS) offer technological solutions that ...
来源: 评论
F2A2: Flexible Fully-decentralized Approximate Actor-critic for Cooperative Multi-agent Reinforcement Learning
arXiv
收藏 引用
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
收藏 引用
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
收藏 引用
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
收藏 引用
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
A review of uncertainty quantification in deep learning: Techniques, applications and challenges
arXiv
收藏 引用
arXiv 2020年
作者: Abdar, Moloud Pourpanah, Farhad Hussain, Sadiq Rezazadegan, Dana Liu, Li Ghavamzadeh, Mohammad Fieguth, Paul Cao, Xiaochun Khosravi, Abbas Rajendra Acharya, U. Makarenkov, Vladimir Nahavandi, Saeid Deakin University Australia College of Mathematics and Statistics Guangdong Key Lab. of Intelligent Information Processing Shenzhen University Shenzhen518060 China Dibrugarh University Dibrugarh India Department of Computer Science and Software Engineering Swinburne University of Technology Melbourne Australia Center for Machine Vision and Signal Analysis University of Oulu Oulu Finland Google research United States Department of Systems Design Engineering University of Waterloo Waterloo Canada State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing China Department of Electronics and Computer Engineering Ngee Ann Polytechnic Clementi Singapore Department of Computer Science University of Quebec in Montreal MontrealQC Canada
—Uncertainty quantification (UQ) plays a pivotal role in the reduction of uncertainties during both optimization and decision making, applied to solve a variety of real-world applications in science and engineering. ... 详细信息
来源: 评论
No One Left Behind: Real-World Federated Class-Incremental Learning
arXiv
收藏 引用
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
Automatic generation of modules of object categorization for autonomous mobile robots
收藏 引用
AIP Conference Proceedings 2013年 第1期1558卷
作者: Anna Gorbenko Ural Federal University Department of Intelligent Systems and Robotics Mathematics and Computer Science Institute Lenin st. 51 620083 Ekaterinburg Russia
Many robotic tasks require advanced systems of visual sensing. Robotic systems of visual sensing must be able to solve a number of different complex problems of visual data analysis. Object categorization is one of su...
来源: 评论
Few-Shot Medical Image Segmentation with High-Fidelity Prototypes
arXiv
收藏 引用
arXiv 2024年
作者: Tang, Song Yan, Shaxu Qi, Xiaozhi Gao, Jianxin Ye, Mao Zhang, Jianwei Zhu, Xiatian IMI Group School of Health Sciences and Engineering University of Shanghai for Science and Technology Shanghai China TAMS Group Department of Informatics Universität Hamburg Hamburg Germany School of Computer Science and Engineering University of Electronic Science and Technology of China Chengdu China Surrey Institute for People-Centred Artificial Intelligence Centre for Vision Speech and Signal Processing University of Surrey Guildford United Kingdom Shenzhen Key Laboratory of Minimally Invasive Surgical Robotics and System Shenzhen Institute of Advanced Technology Chinese Academy of Sciences China
Few-shot Semantic Segmentation (FSS) aims to adapt a pretrained model to new classes with as few as a single labelled training sample per class. Despite the prototype based approaches have achieved substantial success... 详细信息
来源: 评论
Flat Rotman lens for 5G beamforming antenna
Flat Rotman lens for 5G beamforming antenna
收藏 引用
IEEE Asia-Pacific Conference on Antennas and Propagation (APCAP)
作者: Muhammad Kamran Khattak Changhyung Lee Dajung Han Sungtek Kahng Department of Information Technologies Università degli Studi di Milano Doctoral School of Computer Science Crema Italy Doctoral School of Applied Informatics and Applied Mathematics Obuda University Budapest Hungary Antal Bejczy Center for Intelligent Robotics (ABC iRob) Obuda University Budapest Hungary Institute of Mechatronics and Vehicle Engineering Obuda University Budapest Hungary Department of Mathematics and Informatics J. Selye University Komarno Slovakia Department of Information Technologies Università degli Studi di Milano Crema Italy
In this paper, a planar Rotman lens featured as beamforming and multiple beams is presented, aimed at the potential use for 5G communication. The feeding network and the radiating patches are made as a single layer Ta... 详细信息
来源: 评论