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Titlebook: Machine Learning and Intelligent Communication; 7th EAI Internationa Xiaolin Jiang Conference proceedings 2023 ICST Institute for Computer

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發(fā)表于 2025-3-21 18:00:05 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Machine Learning and Intelligent Communication
副標(biāo)題7th EAI Internationa
編輯Xiaolin Jiang
視頻videohttp://file.papertrans.cn/621/620474/620474.mp4
叢書名稱Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engi
圖書封面Titlebook: Machine Learning and Intelligent Communication; 7th EAI Internationa Xiaolin Jiang Conference proceedings 2023 ICST Institute for Computer
描述This book constitutes the refereed post-conference proceedings of the 7.th. International Conference on Machine Learning and Intelligent Computing which was held in October 2022 in Jinhua, China. Due to COVID-19 pandemic the conference was held virtually.. The 16 full papers of MLICOM 2022 were selected from 41 submissions and are clustered in thematical issues on applications of neural network and deep learning; intelligent massive MIMO communications; machine learning algorithms and intelligent networks.
出版日期Conference proceedings 2023
關(guān)鍵詞artificial intelligence; communication systems; computer hardware; computer networks; computer science; c
版次1
doihttps://doi.org/10.1007/978-3-031-30237-4
isbn_softcover978-3-031-30236-7
isbn_ebook978-3-031-30237-4Series ISSN 1867-8211 Series E-ISSN 1867-822X
issn_series 1867-8211
copyrightICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2023
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書目名稱Machine Learning and Intelligent Communication影響因子(影響力)




書目名稱Machine Learning and Intelligent Communication影響因子(影響力)學(xué)科排名




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書目名稱Machine Learning and Intelligent Communication網(wǎng)絡(luò)公開度學(xué)科排名




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Yan Li,Decheng Yang,Baojin Zhang,Zhuo Zhai,Zhixu Luo
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Automated Metal Surface Defect Detection,entation method for patch defect and scratch defect respectively and accurately localize the patch defect on metal surfaces and evaluated using Intersection over Union (IoU). In this project, a total of 3 image segmentation methods are attempted namely threshold-based segmentation, edge-based segmen
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Design and Implementation of Intelligent Truck Based on Azure Kinect,and the spatial coordinates of the object centroid are obtained in real time. The accuracy rate can reach 94.48%, and the target objects of different shapes can be recognized. When the target object is grasped by the robot arm, it can be grasped accurately according to the depth information, and the
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