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Titlebook: Recent Developments in Mechatronics and Intelligent Robotics; Proceedings of Inter Kevin Deng,Zhengtao Yu,John Wang Conference proceedings

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发表于 2025-3-21 18:41:43 | 显示全部楼层 |阅读模式
书目名称Recent Developments in Mechatronics and Intelligent Robotics
副标题Proceedings of Inter
编辑Kevin Deng,Zhengtao Yu,John Wang
视频video
概述Presents the latest research, cutting edge technology of Mechatronics and Intelligent Robotics.Contributed by academicians and trusted experts in the field.Researchers and Academicians and Industry ex
丛书名称Advances in Intelligent Systems and Computing
图书封面Titlebook: Recent Developments in Mechatronics and Intelligent Robotics; Proceedings of Inter Kevin Deng,Zhengtao Yu,John Wang Conference proceedings
描述.This book is a collection of proceedings of the International Conference on Mechatronics and Intelligent Robotics (ICMIR2018), held in Kunming, China during May 19–20, 2018. It consists of 155 papers, which have been categorized into 6 different sections: Intelligent Systems, Robotics, Intelligent Sensors & Actuators, Mechatronics, Computational Vision and Machine Learning, and Soft Computing. .. The volume covers the latest ideas and innovations both from the industrial and academic worlds, as well as shares the best practices in the fields of mechanical engineering, mechatronics, automatic control, IOT and its applications in industry, electrical engineering, finite element analysis and computational engineering. The volume covers key research outputs, which delivers a wealth of new ideas and food for thought to the readers... .
出版日期Conference proceedings 2019
关键词Mechatronics; Intelligent Robotics; Automation & Control; Sensors; Actuators
版次1
doihttps://doi.org/10.1007/978-3-030-00214-5
isbn_softcover978-3-030-00213-8
isbn_ebook978-3-030-00214-5Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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A New Active Learning Semi-supervised Community Detection Algorithm in Complex Networksis demonstrated with four real-world networks and a artificial network benchmark. Extensive experiments show that it effectively improves community detection results and has lower computational complexity compared with some community detection algorithms.
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2194-5357 ts in the field.Researchers and Academicians and Industry ex.This book is a collection of proceedings of the International Conference on Mechatronics and Intelligent Robotics (ICMIR2018), held in Kunming, China during May 19–20, 2018. It consists of 155 papers, which have been categorized into 6 dif
发表于 2025-3-22 09:26:30 | 显示全部楼层
Effective Prediction of Microblog User Retweet Behaviors Based on Markov Random Fieldwe propose an effective prediction framework based on Markov Random Field for finding the global optimal solution to improve the prediction accuracy. Under the proposed method, we systematically analyze the various factors affecting the retweet behavior and the retweet constraints between users, and
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Denoising Point Cloud Based on the Connexity of Spatial Grid based on the connexity of spatial grid was proposed. Firstly, the concept of connected region in the binary image was extended to 3D point cloud model, divided the point cloud model into uniform space hexahedron, created the concept of adjacent lattice cell, then determined the pixel value of cell
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A New Active Learning Semi-supervised Community Detection Algorithm in Complex Networksrior information to improve the performance of community detection. But how to obtain these prior information is a challenging problem. In this paper, we present a new active learning semi-supervised community detection algorithm based on node relevance and similarities measures. Firstly, it calcula
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