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Titlebook: Machine Learning for Intelligent Multimedia Analytics; Techniques and Appli Pardeep Kumar,Amit Kumar Singh Book 2021 Springer Nature Singap

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发表于 2025-3-21 19:50:34 | 显示全部楼层 |阅读模式
书目名称Machine Learning for Intelligent Multimedia Analytics
副标题Techniques and Appli
编辑Pardeep Kumar,Amit Kumar Singh
视频video
概述Presents applications of machine learning techniques in processing multimedia large-scale data.Discusses new challenges faced by researchers in dealing with multimedia data.Provides innovative solutio
丛书名称Studies in Big Data
图书封面Titlebook: Machine Learning for Intelligent Multimedia Analytics; Techniques and Appli Pardeep Kumar,Amit Kumar Singh Book 2021 Springer Nature Singap
描述.This book presents applications of machine learning techniques in processing multimedia large-scale data. Multimedia such as text, image, audio, video, and graphics stands as one of the most demanding and exciting aspects of the information era. The book discusses new challenges faced by researchers in dealing with these large-scale data and also presents innovative solutions to address several potential research problems, e.g., enabling comprehensive visual classification to fill the semantic gap by exploring large-scale data, offering a promising frontier for detailed multimedia understanding, as well as extract patterns and making effective decisions by analyzing the large collection of data..
出版日期Book 2021
关键词Multimedia Analytics; Big Data; IoT; Healthcare; Urban Computing; Digital Forensics; Security and Privacy;
版次1
doihttps://doi.org/10.1007/978-981-15-9492-2
isbn_softcover978-981-15-9494-6
isbn_ebook978-981-15-9492-2Series ISSN 2197-6503 Series E-ISSN 2197-6511
issn_series 2197-6503
copyrightSpringer Nature Singapore Pte Ltd. 2021
The information of publication is updating

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Studies in Big Datahttp://image.papertrans.cn/m/image/620625.jpg
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Secure Image Transmission in Wireless Network Using Conventional Neural Network and DOST,iscrete orthonormal Stockwell transform (DOST) and CNN. For image encryption, pixel shuffling method and Arnold transform are used in DOST domain. The proposed methods are compared and analyzed the performance using mean error, PSNR and Entropy difference. The obtained results are better in compared to existing methods.
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Book 2021o, and graphics stands as one of the most demanding and exciting aspects of the information era. The book discusses new challenges faced by researchers in dealing with these large-scale data and also presents innovative solutions to address several potential research problems, e.g., enabling compreh
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Robust General Twin Support Vector Machine with Pinball Loss Function,positive definite. The incorporation of the structural risk minimization principle via introduction of the regularisation term leads to the improved generalization performance of the proposed Pin-RGTSVM. Numerical experiments and statistical evaluation on the real world benchmark datasets show the efficacy of the proposed Pin-RGTSVM.
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