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检索条件"机构=Institute of artificial intelligence and robotics"
3901 条 记 录,以下是31-40 订阅
排序:
SCTF-Det: Siamese Center-Based Detector with Transformer and Feature Fusion for Object-Level Change Detection
SCTF-Det: Siamese Center-Based Detector with Transformer and...
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2023 China Automation Congress, CAC 2023
作者: Huo, Jiaxin Sun, Lihang Liu, Jianyi Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University Xi'an China
Current Scene Change Detection(SCD) methods are widely used in various subject areas, with detection granularity mostly limited to pixel-level. However, for certain practical applications such as garbage detection and... 详细信息
来源: 评论
A Novel Map Representation for Automatic Construction of Topological Map and Lane-Level Route Planning
A Novel Map Representation for Automatic Construction of Top...
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2023 China Automation Congress, CAC 2023
作者: Sun, Jian Xue, Jianru Li, Gengxin Liu, Jingcheng Institute of Artificial Intelligence and Robotics Xi' An Jiaotong University Xi'an China
Traditional road-level topological maps cannot meet the demand for high precision navigation services required by human drivers and autonomous vehicles. Meanwhile, current enhanced lane-level topological maps with red... 详细信息
来源: 评论
Learning to Embed Seen/Unseen Compositions based on Graph Networks
Learning to Embed Seen/Unseen Compositions based on Graph Ne...
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2023 China Automation Congress, CAC 2023
作者: Jiang, Dongyao Chen, Hui Ma, Yongqiang Jing, Haodong Zheng, Nanning Institute of Artificial Intelligence and Robotics Xi'An Jiaotong University Xi'an China
Composability allows known concepts to form newer and more complex ones. This coupling process is the research interests of Compositional Zero-Shot Learning (CZSL). The goal can be described as building a classifier f... 详细信息
来源: 评论
U-YOLO: Improved YOLOv5 for Small Object Detection on UAV-Captured Images  1st
U-YOLO: Improved YOLOv5 for Small Object Detection on UAV-...
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1st International Conference on Cognitive Computation and Systems, ICCCS 2022
作者: Zhang, Guowei Chen, Xingyu Tan, Xun Zhang, Jiahao Lan, Xuguang Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Xi’an China
Small object detection on drone-captured images is a recently popular and challenging task. From the drone’s perspective, the object scale varies significantly, and tiny objects lack distinguishable appearance inform... 详细信息
来源: 评论
Atten-ganCV: An End-to-End Close-Coupled Image-Generating Cross-View Network
Atten-ganCV: An End-to-End Close-Coupled Image-Generating Cr...
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2023 China Automation Congress, CAC 2023
作者: Song, Wenjie Xue, Jianru Institute of Artificial Intelligence and Robotics Xi'An Jiaotong University Xi'an China
Cross-view geo-localization aims to match the query input ground-view image and the aerial-view images in the reference dataset one by one to determine the ground image's geographic location. This research is extr... 详细信息
来源: 评论
Learning Object Relation Graph and Goal-Aware Policy For Visual Room Rearrangement
Learning Object Relation Graph and Goal-Aware Policy For Vis...
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2023 China Automation Congress, CAC 2023
作者: Wang, Beibei Wang, Xiaohan Liu, Yuehu College of Artificial Intelligence Xi'an Jiaotong University Xi'an China Institute of Artificial Intelligence and Robotics College of Artificial Intelligence Xi'an Jiaotong University Xi'an China
Embodied AI, where agents accomplish specific tasks through interaction with their surrounding environment, is attracting attention in the community. As a more comprehensive and practical embodied task, visual room re... 详细信息
来源: 评论
Safe Multi-Agent Reinforcement Learning for Behavior-Based Cooperative Navigation
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IEEE robotics and Automation Letters 2025年 第6期10卷 6256-6263页
作者: Dawood, Murad Pan, Sicong Dengler, Nils Zhou, Siqi Schoellig, Angela P. Bennewitz, Maren University of Bonn Humanoid Robots Lab Bonn53113 Germany Lamarr Institute for Machine Learning and Artificial Intelligence The Center for Robotics Bonn53113 Germany Technical University of Munich Learning Systems and Robotics Lab Munchen80333 Germany
In this letter, we address the problem of behavior-based cooperative navigation of mobile robots usingsafe multi-agent reinforcement learning (MARL). Our work is the first to focus on cooperative navigation without in... 详细信息
来源: 评论
DO GENERATED DATA ALWAYS HELP CONTRASTIVE LEARNING?  12
DO GENERATED DATA ALWAYS HELP CONTRASTIVE LEARNING?
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12th International Conference on Learning Representations, ICLR 2024
作者: Wang, Yifei Zhang, Jizhe Wang, Yisen School of Mathematical Sciences Peking University China Institute of Artificial Intelligence and Robotics Xi'an Jiaotong University China National Key Lab of General Artificial Intelligence School of Intelligence Science and Technology Peking University China Institute for Artificial Intelligence Peking University China
Contrastive Learning (CL) has emerged as one of the most successful paradigms for unsupervised visual representation learning, yet it often depends on intensive manual data augmentations. With the rise of generative m... 详细信息
来源: 评论
Event-enhanced synthetic aperture imaging
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Science China(Information Sciences) 2025年 第3期68卷 388-390页
作者: Siqi LI Shaoyi DU Jun-Hai YONG Yue GAO Beijing National Research Center for Information Science and Technology School of SoftwareTsinghua University Institute for Brain and Cognitive Sciences Beijing Laboratory of Brain and Cognitive IntelligenceTsinghua University National Key Laboratory of Human-Machine Hybrid Augmented Intelligence National Engineering Research Center for Visual Information and ApplicationsInstitute of Artificial Intelligence and Robotics Xi'an Jiaotong University
Synthetic aperture imaging(SAI) methods aim to see through dense occlusions and reconstruct the target scene behind occlusions. Traditional frame-based SAI methods,e.g., DeOccNet [1], take the occluded light field ima...
来源: 评论
A Sparsity-Aware Autonomous Path Planning Accelerator with Algorithm-Architecture Co-Design  24
A Sparsity-Aware Autonomous Path Planning Accelerator with A...
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43rd International Conference on Computer-Aided Design, ICCAD 2024
作者: Zhang, Yanjun Niu, Xiaoyu Zhang, Yifan Tian, Hongzheng Yu, Bo Liu, Shaoshan Huang, Sitao Beijing Institute of Technology China University of California Irvine United States Shenzhen Institute of Artificial Intelligence and Robotics for Society China
Path planning is a critical task in autonomous driving systems that is most susceptible to real-time constraints but often demands computationally intensive mathematical solvers, two contradictory goals. This conflict... 详细信息
来源: 评论