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Titlebook: Cognitive Computation and Systems; First International Fuchun Sun,Jianmin Li,Zhongyi Chu Conference proceedings 2023 The Editor(s) (if app

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发表于 2025-3-21 17:07:22 | 显示全部楼层 |阅读模式
书目名称Cognitive Computation and Systems
副标题First International
编辑Fuchun Sun,Jianmin Li,Zhongyi Chu
视频videohttp://file.papertrans.cn/229/228998/228998.mp4
丛书名称Communications in Computer and Information Science
图书封面Titlebook: Cognitive Computation and Systems; First International  Fuchun Sun,Jianmin Li,Zhongyi Chu Conference proceedings 2023 The Editor(s) (if app
描述This volume constitutes selected papers presented during the First International Conference on Cognitive Computation and Systems, ICCCS 2022, held in Beijing, China, in October 2022..The 31 papers were thoroughly reviewed and selected from the 75 submissions. The papers are organized in topical sections on ​computer vision; decision making and cognitive computation; robot and autonomous vehicle..
出版日期Conference proceedings 2023
关键词artificial intelligence; machine learning; robotics; computer vision; robotic autonomy; cognitive science
版次1
doihttps://doi.org/10.1007/978-981-99-2789-0
isbn_softcover978-981-99-2788-3
isbn_ebook978-981-99-2789-0Series ISSN 1865-0929 Series E-ISSN 1865-0937
issn_series 1865-0929
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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A Novel Autoencoder for Task-Driven Object Segmentationds can only recognize and segment one class of objects, but cannot segment the other classes of objects in the same image. To address this issue, this paper proposes a novel autoencoder to perform task-driven object segmentation, in which a control signal is added to the decoder to determine which c
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Feedback Attention-Augmented Bilateral Network for Amodal Instance Segmentationarts of each object instance. Many modern computer vision methods demonstrate excellent performance by using the mechanism of looking and thinking twice and the attention mechanism. In this paper, we propose a feedback attention-augmented bilateral network. Specifically, after the convolutional netw
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PointNetX: Part Segmentation Based on PointNet Promotionet, a pioneer in point cloud processing, uses max pooling to address the disorder of point clouds. However, PointNet‘s method of mapping points to high-dimensional space, and then obtaining global features through maximum pooling still leads to a large loss of feature information. To this end, we su
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Shape and Pose Reconstruction of Robotic In-Hand Objects from a Single Depth Cameraritically important for robotic in-hand manipulation. However, in-hand objects have self-occlusion, making it challenging to perceive their complete shape and posture. To address this challenge, this work proposed a point-clouds processing framework to achieve shape completion and pose estimation of
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“Gongzhu” Strategy Based on Convolutional Neural Networkd-showing and card-playing. The behavior of card-showing determines the strategy of card-playing, and the whole game process is highly reversible. This paper proposes a deep learning-based game algorithm of “Gongzhu”. According to the functional characteristics, the network structure of card-showing
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