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检索条件"机构=Intelligent Robotics and Computer Vision Group Department of Computer Science and Mathematics"
242 条 记 录,以下是111-120 订阅
排序:
Boosting Scalable Gradient Features for Adaptive Real-Time Tracking
Boosting Scalable Gradient Features for Adaptive Real-Time T...
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2011 IEEE International Conference on robotics and Automation(2011年IEEE世界机器人与自动化大会 ICRA 2011)
作者: Dominik A. Klein Armin B. Cremers Intelligent Vision Systems Group Department of Computer Science IIIRheinische Friedrich-Wilhelms-Universit(a)t Bonn53117 BonnGermany
Recently, several image gradient and edge based features have been introduced. In unison, they all discovered that object shape is a strong cue for recognition and tracking. Generally their basic feature extraction re... 详细信息
来源: 评论
One deep music representation to rule them all? A comparative analysis of different representation learning strategies
arXiv
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arXiv 2018年
作者: Kim, Jaehun Urbano, Julián Liem, Cynthia C.S. Hanjalic, Alan Multimedia Computing Group Department of Intelligent Systems Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology
Inspired by the success of deploying deep learning in the fields of computer vision and Natural Language Processing, this learning paradigm has also found its way into the field of Music Information Retrieval. In orde... 详细信息
来源: 评论
Clustering of Motion Trajectories by a Distance Measure Based on Semantic Features
Clustering of Motion Trajectories by a Distance Measure Base...
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IEEE-RAS International Conference on Humanoid Robots
作者: Christoph Zelch Jan Peters Oskar von Stryk Department of Computer Science TU Darmstadt Hochschulstr. 10 Simulation Systems Optimization and Robotics Group Darmstadt Germany Department of Computer Science TU Darmstadt Hochschulstr. 10 Intelligent Autonomous Systems Group Darmstadt 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...
来源: 评论
Fast-moving object counting with an event camera
arXiv
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arXiv 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
LiDAR-based drone navigation with reinforcement learning
TechRxiv
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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
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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...
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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...
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LiDAR-based drone navigation with reinforcement learning
arXiv
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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
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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