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Titlebook: Intelligent Robotics and Applications; 15th International C Honghai Liu,Zhouping Yin,Weihong Ren Conference proceedings 2022 The Editor(s)

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發(fā)表于 2025-3-21 18:37:49 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Intelligent Robotics and Applications
副標(biāo)題15th International C
編輯Honghai Liu,Zhouping Yin,Weihong Ren
視頻videohttp://file.papertrans.cn/470/469898/469898.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Intelligent Robotics and Applications; 15th International C Honghai Liu,Zhouping Yin,Weihong Ren Conference proceedings 2022 The Editor(s)
描述The 4-volume set LNAI 13455 - 13458 constitutes the proceedings of the 15.th.?International Conference on Intelligent Robotics and Applications, ICIRA 2022, which took place in Harbin China, during August 2022..The 284 papers included in these proceedings were carefully reviewed and selected from 442 submissions. They were organized in topical sections as follows: Robotics, Mechatronics, Applications, Robotic Machining, Medical Engineering, Soft and Hybrid Robots, Human-robot Collaboration, Machine Intelligence, ?and Human Robot Interaction..
出版日期Conference proceedings 2022
關(guān)鍵詞artificial intelligence; automation; computer hardware; computer science; computer systems; computer visi
版次1
doihttps://doi.org/10.1007/978-3-031-13844-7
isbn_softcover978-3-031-13843-0
isbn_ebook978-3-031-13844-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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https://doi.org/10.1007/978-3-031-13844-7artificial intelligence; automation; computer hardware; computer science; computer systems; computer visi
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發(fā)表于 2025-3-22 04:17:16 | 只看該作者
978-3-031-13843-0The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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發(fā)表于 2025-3-22 05:49:35 | 只看該作者
Intelligent Robotics and Applications978-3-031-13844-7Series ISSN 0302-9743 Series E-ISSN 1611-3349
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發(fā)表于 2025-3-22 09:38:59 | 只看該作者
An End-to-End Object Detector with Spatiotemporal Context Learning for Machine-Assisted Rehabilitatihas higher real-time performance than DETR and obtains the competitive detection accuracy on the ImageNet VID benchmark. Some typical samples from the NTU RGB-D 60 dataset are selected to build a new limb-detection dataset for further evaluation. The results show the effectiveness of the proposed detector in the rehabilitation scenarios.
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A Study of Virtual Reality Systems for Attention Stabilizationp between attention, eye-movement and prefrontal. It verified the rationality of the combined method of virtual reality technology and eye-tracking technology in the content of attentional stability test, and provided scientific data support and experimental suggestions for future attention deficit disorder to conduct attentional stability test.
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