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Titlebook: Emerging Technologies in Data Mining and Information Security; Proceedings of IEMIS Paramartha Dutta,Abhishek Bhattacharya,Wen-Cheng L Conf

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發(fā)表于 2025-3-21 17:02:02 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Emerging Technologies in Data Mining and Information Security
副標(biāo)題Proceedings of IEMIS
編輯Paramartha Dutta,Abhishek Bhattacharya,Wen-Cheng L
視頻videohttp://file.papertrans.cn/309/308447/308447.mp4
概述Presents recent research in the field of data mining and information security.Discusses the outcomes of IEMIS 2022, held in Kolkata, India.Serves as a reference resource for researchers and practition
叢書(shū)名稱Advances in Intelligent Systems and Computing
圖書(shū)封面Titlebook: Emerging Technologies in Data Mining and Information Security; Proceedings of IEMIS Paramartha Dutta,Abhishek Bhattacharya,Wen-Cheng L Conf
描述.This book features research papers presented at the International Conference on Emerging Technologies in Data Mining and Information Security (IEMIS 2022) held at Institute of Engineering & Management, Kolkata, India, during February 23–25, 2022.?The book is organized in three volumes?and includes high-quality research work by academicians and industrial experts in the field of computing and communication, including full-length papers, research-in-progress papers, and case studies related to all the areas of data mining, machine learning, Internet of Things (IoT), and information security..
出版日期Conference proceedings 2023
關(guān)鍵詞Information Retrieval; Pattern Recognition; Data Science and Data Analytics; Network Security and Telec
版次1
doihttps://doi.org/10.1007/978-981-19-4676-9
isbn_softcover978-981-19-4675-2
isbn_ebook978-981-19-4676-9Series ISSN 2194-5357 Series E-ISSN 2194-5365
issn_series 2194-5357
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

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Tomodensitometry with X- and Gamma-Raysn of the traveling salesman problem (TSP), with one condition that it is not required for a sales person to travel all cities of the network. Our main purpose is to optimize the total profit and cost of the traveling. Here we are focusing on that in the case of TSPs; in real world scenario it is not
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https://doi.org/10.1007/978-1-4615-4847-8ers are effective unsupervised learning method which encode an input into a lower dimensional representation. This representation input consist of input as features are useful for image processing applications. The size of hidden representation is lesser then the original image that’s under complete
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Quantitative Analysis of Delaminations,the vital nature of fuel. This research explores room for advancement in exploiting consumption data and generating smart results powered by state-of-the-art algorithms and sensors. The line of experimentation for this problem statement is focused on enabling users to interpret their power consumpti
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