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Titlebook: Intelligent Computing and Applications; Proceedings of ICDIC B. Narendra Kumar Rao,R. Balasubramanian,Richi Nay Conference proceedings 2023

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發(fā)表于 2025-3-21 19:19:32 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Intelligent Computing and Applications
副標(biāo)題Proceedings of ICDIC
編輯B. Narendra Kumar Rao,R. Balasubramanian,Richi Nay
視頻videohttp://file.papertrans.cn/470/469498/469498.mp4
概述Presents research works in the field of data sciences.Results of ICDIC 2020 held in Sree Vidyanikethan Engineering College, Tirupati, India.Serves as a reference for researchers and practitioners in a
叢書名稱Smart Innovation, Systems and Technologies
圖書封面Titlebook: Intelligent Computing and Applications; Proceedings of ICDIC B. Narendra Kumar Rao,R. Balasubramanian,Richi Nay Conference proceedings 2023
描述This book presents novel work of academicians, researchers, industry professionals, practitioners, and budding engineers to disseminate the most recent innovations, trends, and concerns along with the present-day challenges and the solving approaches for implementation in the domains of data science, intelligent computing, and computer networks and security. It is a collection of selected high-quality research papers from the International Conference on Data Science, Intelligent Computing and Cyber Security (ICDIC 2020) organized by Sree Vidyanikethan Engineering College, Tirupati, India, during 27–29 February 2020. It discusses the latest challenges and solutions in the field of data innovation, data management, data analysis, data security, and intelligent methods and applications..
出版日期Conference proceedings 2023
關(guān)鍵詞Artificial Intelligence; Expert Systems; Computational Intelligence; Machine Learning; Deep Learning; Cog
版次1
doihttps://doi.org/10.1007/978-981-19-4162-7
isbn_softcover978-981-19-4164-1
isbn_ebook978-981-19-4162-7Series ISSN 2190-3018 Series E-ISSN 2190-3026
issn_series 2190-3018
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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,Classification of?Credit Card Frauds Using Autoencoded Features,r (IC3) had received 2,211,396 complaints culminating in a $13.3 billion loss which is approximately equal to cumulative loss from 2016–19. Credit card fraud detection is hindered by concept drift, uneven class distribution, identifying a smaller set of features, and detecting real-time frauds. To o
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Data-Driven Approach to Deflate Consumption in Delay Tolerant Networks,ous frameworks that could require steady accessibility. The capacity to move, or course, information from a communicating end to a tolerant end is an urgent limit of all data exchanging frameworks should have. Deferral-tolerant systems (DTNs) are inspected by their deficiency of accessibility, provo
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Design of a Deep Network Model for Weed Classification,arming is to predict the precise crop and weed location over the farmland. Here, a novel dense convolutional neural networks (DCNN)-based network is proposed to differentiate weeds from crops. The overall architecture of crop and weed prediction is extensive, with enormous parameters requiring a lon
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E-Voting System Using U-Net Architecture with Blockchain Technology,ypes of voting system: paper ballots and electronic voting machines (EVMs), both of which have similar drawbacks. The provision of security in a digital voting system has long been a major concern. In the proposed work, implemented an interface. Firstly, the user has to register after which they wil
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