咨询与建议

限定检索结果

文献类型

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

馆藏范围

  • 289 篇 电子文献
  • 0 种 纸本馆藏

日期分布

学科分类号

  • 178 篇 工学
    • 117 篇 计算机科学与技术...
    • 103 篇 软件工程
    • 55 篇 控制科学与工程
    • 46 篇 光学工程
    • 42 篇 生物工程
    • 40 篇 信息与通信工程
    • 33 篇 生物医学工程(可授...
    • 18 篇 电气工程
    • 16 篇 电子科学与技术(可...
    • 13 篇 仪器科学与技术
    • 12 篇 机械工程
    • 12 篇 动力工程及工程热...
    • 11 篇 交通运输工程
    • 8 篇 化学工程与技术
    • 7 篇 力学(可授工学、理...
    • 7 篇 土木工程
    • 6 篇 建筑学
  • 115 篇 理学
    • 47 篇 数学
    • 46 篇 生物学
    • 41 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...
  • 7 篇 法学
    • 7 篇 社会学
  • 7 篇 农学
  • 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 robot kinematics
  • 7 篇 training
  • 6 篇 robots
  • 6 篇 system-on-chip
  • 6 篇 mathematics
  • 6 篇 field programmab...

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

  • 278 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"
289 条 记 录,以下是131-140 订阅
排序:
LiDAR-based drone navigation with reinforcement learning
TechRxiv
收藏 引用
TechRxiv 2023年
作者: Miera, Pawel Szolc, Hubert Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland
Reinforcement learning is of increasing importance in the field of robot control and simulation plays a key role in this process. In the unmanned aerial vehicles (UAVs, drones), there is also an increase in the number... 详细信息
来源: 评论
PointPillars Backbone Type Selection For Fast and Accurate LiDAR Object Detection
TechRxiv
收藏 引用
TechRxiv 2022年
作者: Lis, Konrad Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland
3D object detection from LiDAR sensor data is an important topic in the context of autonomous cars and drones. In this paper, we present the results of experiments on the impact of backbone selection of a deep convolu... 详细信息
来源: 评论
Signal propagation in transformers: theoretical perspectives and the role of rank collapse  22
Signal propagation in transformers: theoretical perspectives...
收藏 引用
Proceedings of the 36th International Conference on Neural Information Processing Systems
作者: Lorenzo Noci Sotiris Anagnostidis Luca Biggio Antonio Orvieto Sidak Pal Singh Aurelien Lucchi Dept of Computer Science ETH Zürich Dept of Computer Science ETH Zürich and Robotics & ML CSEM SA Alpnach Switzerland Dept of Computer Science ETH Zürich and MPI for Intelligent Systems Tübingen Department of Mathematics and Computer Science University of Basel
Transformers have achieved remarkable success in several domains, ranging from natural language processing to computer vision. Nevertheless, it has been recently shown that stacking self-attention layers — the distin...
来源: 评论
LiDAR-based drone navigation with reinforcement learning
arXiv
收藏 引用
arXiv 2023年
作者: Miera, Pawel Szolc, Hubert Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland
Reinforcement learning is of increasing importance in the field of robot control and simulation plays a key role in this process. In the unmanned aerial vehicles (UAVs, drones), there is also an increase in the number... 详细信息
来源: 评论
Fast-moving object counting with an event camera
TechRxiv
收藏 引用
TechRxiv 2022年
作者: Bialik, Kamil Kowalczyk, Marcin Blachut, Krzysztof Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland
This paper proposes the use of an event camera as a component of a vision system that enables counting of fast-moving objects – in this case, falling corn grains. These type of cameras transmit information about the ... 详细信息
来源: 评论
PointPillars Backbone Type Selection For Fast and Accurate LiDAR Object Detection
arXiv
收藏 引用
arXiv 2022年
作者: Lis, Konrad Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland
3D object detection from LiDAR sensor data is an important topic in the context of autonomous cars and drones. In this paper, we present the results of experiments on the impact of backbone selection of a deep convolu... 详细信息
来源: 评论
Clustering of Motion Trajectories by a Distance Measure Based on Semantic Features
arXiv
收藏 引用
arXiv 2024年
作者: Zelch, Christoph Peters, Jan von Stryk, Oskar Simulation Systems Optimization and Robotics Group Department of Computer Science TU Darmstadt Hochschulstr. 10 Darmstadt64289 Germany Intelligent Autonomous Systems Group Department of Computer Science TU Darmstadt Hochschulstr. 10 Darmstadt64289 Germany
Clustering of motion trajectories is highly relevant for human-robot interactions as it allows the anticipation of human motions, fast reaction to those, as well as the recognition of explicit gestures. Further, it al... 详细信息
来源: 评论
Visual attention-based robot navigation using information sampling
Visual attention-based robot navigation using information sa...
收藏 引用
IEEE International Workshop on intelligent Robots and Systems (IROS)
作者: N. Winters J. Santos-Victor Computer Vision and Robotics Group Department of Computer Science University of Dublin-Trinity College Dublin Ireland Instituto de Sistemas e Robótica Instituto Superior Técnico Lisboa Portugal
Presents a method whereby an autonomous mobile robot automatically selects the most informative data from a set of images acquired a priori, using a statistical method termed information sampling. These data could be ... 详细信息
来源: 评论
Skeletal Human Action Recognition using Hybrid Attention based Graph Convolutional Network
arXiv
收藏 引用
arXiv 2022年
作者: Xing, Hao Burschka, Darius Technical University of Munich Machine Vision and Perception Group Munich Institute of Robotics and Machine Intelligence Department of Computer Science Parkring 13 Munich85748 Germany
In skeleton-based action recognition, Graph Convolutional Networks model human skeletal joints as vertices and connect them through an adjacency matrix, which can be seen as a local attention mask. However, in most ex... 详细信息
来源: 评论
Learning representations that are closed-form Monge mapping optimal with application to domain adaptation
arXiv
收藏 引用
arXiv 2023年
作者: Struckmeier, Oliver Redko, Ievgen Mallasto, Anton Arndt, Karol Heinonen, Markus Kyrki, Ville Aalto University Finland Intelligent Robotics Group Finland Noah's Ark Lab Huawei Technologies Hong Kong Department of Computer Science Finland
Optimal transport (OT) is a powerful geometric tool used to compare and align probability measures following the least effort principle. Despite its widespread use in machine learning (ML), OT problem still bears its ... 详细信息
来源: 评论