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面向智能多媒体分析的机器学习(英文版)
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本资料主要探讨了机器学习在智能多媒体分析中的应用,涵盖了从图像、音频到文本等多种多媒体数据的处理和分析。 资料中介绍了使用卷积神经网络进行图像识别、基于离散正交Stockwell变换和CNN的图像加密、KannadaRes - Next框架对Kannada手写数字的识别、利用常规神经网络和DOST的图像安全传输、基于Pinball损失函数的鲁棒通用孪生支持向量机、基于模糊逻辑和非线性滤波的噪声抗阈值技术、使用卷积神经网络进行音频事件检测、基于K - means++和Memetic算法的多语言场景文本检测等内容。通过这些技术,可以实现对多媒体数据的有效分析和处理,为各种应用提供支持。本书为从事相关研究的人员提供了有价值的参考。
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Studies in Big Data 82
Pardeep Kumar
Amit Kumar Singh Editors
Machine
Learning
for Intelligent
Multimedia
Analytics
Techniques and Applications
Studies in Big Data
Volume 82
Series Editor
Janusz Kacprzyk, Polish Academy of Sciences, Warsaw, Poland
The series “Studies in Big Data” (SBD) publishes new developments and advances
in the various areas of Big Data- quickly and with a high quality. The intent is to
cover the theory, research, development, and applications of Big Data, as embedded
in the fields of engineering, computer science, physics, economics and life sciences.
The books of the series refer to the analysis and understanding of large, complex,
and/or distributed data sets generated from recent digital sources coming from
sensors or other physical instruments as well as simulations, crowd sourcing, social
networks or other internet transactions, such as emails or video click streams and
other. The series contains monographs, lecture notes and edited volumes in Big
Data spanning the areas of computational intelligence including neural networks,
evolutionary computation, soft computing, fuzzy systems, as well as artificial
intelligence, data mining, modern statistics and Operations research, as well as
self-organizing systems. Of particular value to both the contributors and the
readership are the short publication timeframe and the world-wide distribution,
which enable both wide and rapid dissemination of research output.
The books of this series are reviewed in a single blind peer review process.
Indexed by zbMATH.
All books published in the series are submitted for consideration in Web of Science.
More information about this series at http://www.springer.com/series/11970
Pardeep Kumar
•
Amit Kumar Singh
Editors
Machine Learning
for Intelligent Multimedia
Analytics
Techniques and Applications
123
Editors
Pardeep Kumar
Department of Computer Science and
Engineering and Information Technology
Jaypee University of Information
Technology
Solan, Himachal Pradesh, India
Amit Kumar Singh
Department of Computer Science
and Engineering
National Institute of Technology
Patna, Bihar, India
ISSN 2197-6503 ISSN 2197-6511 (electronic)
Studies in Big Data
ISBN 978-981-15-9491-5 ISBN 978-981-15-9492-2 (eBook)
https://doi.org/10.1007/978-981-15-9492-2
© Springer Nature Singapore Pte Ltd. 2021
This work is subject to copyright. All rights are reserved by the Publisher, whether the whole or part
of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations,
recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission
or information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar
methodology now known or hereafter developed.
The use of general descriptive names, registered names, trademarks, service marks, etc. in this
publication does not imply, even in the absence of a specific statement, that such names are exempt from
the relevant protective laws and regulations and therefore free for general use.
The publisher, the authors and the editors are safe to assume that the advice and information in this
book are believed to be true and accurate at the date of publication. Neither the publisher nor the
authors or the editors give a warranty, expressed or implied, with respect to the material contained
herein or for any errors or omissions that may have been made. The publisher remains neutral with regard
to jurisdictional claims in published maps and institutional affiliations.
This Springer imprint is published by the registered company Springer Nature Singapore Pte Ltd.
The registered company address is: 152 Beach Road, #21-01/04 Gateway East, Singapore 189721,
Singapore
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