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Titlebook: Data Science and Security; Proceedings of IDSCS Samiksha Shukla,Aynur Unal,Dong Seog Han Conference proceedings 2021 The Editor(s) (if appl

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书目名称Data Science and Security
副标题Proceedings of IDSCS
编辑Samiksha Shukla,Aynur Unal,Dong Seog Han
视频video
概述Presents research works in the field of data science and computational security.Gives results of IDSCS 2021 held at CHRIST University, India, during March 2021.Serves as a reference for researchers an
丛书名称Lecture Notes in Networks and Systems
图书封面Titlebook: Data Science and Security; Proceedings of IDSCS Samiksha Shukla,Aynur Unal,Dong Seog Han Conference proceedings 2021 The Editor(s) (if appl
描述.This book presents the best-selected papers presented at the International Conference on Data Science, Computation and Security (IDSCS-2021), organized by the Department of Data Science, CHRIST (Deemed to be University), Pune Lavasa Campus, India, during April 16–17, 2021. The proceeding is targeting the current research works in the areas of data science, data security, data analytics, artificial intelligence, machine learning, computer vision, algorithms design, computer networking, data mining, big data, text mining, knowledge representation, soft computing, and cloud computing..
出版日期Conference proceedings 2021
关键词Data Science; Artificial Intelligence; Machine Learning; Quantum Computing; Data and Network Security; Co
版次1
doihttps://doi.org/10.1007/978-981-16-4486-3
isbn_softcover978-981-16-4485-6
isbn_ebook978-981-16-4486-3Series ISSN 2367-3370 Series E-ISSN 2367-3389
issn_series 2367-3370
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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Lecture Notes in Networks and Systemshttp://image.papertrans.cn/d/image/263108.jpg
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https://doi.org/10.1007/978-1-4939-8618-7 abnormal RBCs, the first step in this algorithm identifies the regions of interest depending on morphology operations and the second step uses the rotate features to verify that the detected object is an abnormal RBCs. Two criteria were used to measure detection accuracy depending on the detection
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https://doi.org/10.1007/978-1-4939-8639-2tack. This attack is meant to temporarily or indefinitely make unavailable a machine or network resources thereby making the system inaccessible. In this paper, an intrusion detection system is built using Deep Learning approaches Deep neural network and Convolutional Neural Network to detect DoS at
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Parsing Compound–Protein Bioactivity Tables healthcare helps medical professionals monitor patients and provide services remotely. With the increased adoption of IoMT comes an increased risk profile. Private and confidential medical data is gathered across various IoMT devices and transmitted to medical servers. Privacy breach or unauthorize
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https://doi.org/10.1007/978-3-031-37499-9sis and reduce mortality rates. This paper concerns sensitivity analysis on an existing cervical cancer risk classification algorithm with respect to the number of epochs, number of neurons in the input layer (NIN), and number of neurons in the hidden layer (NNIHL). Sensitivity analysis is used to a
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