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245 1 0 _aData Science and Network Engineering
_h[electronic resource] :
_bProceedings of ICDSNE 2023 /
_cedited by Suyel Namasudra, Munesh Chandra Trivedi, Ruben Gonzalez Crespo, Pascal Lorenz.
250 _a1st ed. 2024.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2024.
300 _aXIX, 527 p. 247 illus., 184 illus. in color.
_bonline resource.
336 _atext
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337 _acomputer
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338 _aonline resource
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347 _atext file
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490 1 _aLecture Notes in Networks and Systems,
_x2367-3389 ;
_v791
505 0 _aPart 1: Computational Intelligence -- Chapter 1: Evaluation of Hand-crafted Features for the Classification of Spam SMS in Dravidian Languages -- Chapter 2: Training Algorithms for Mixtures of Normalizing Flows -- Chapter 3: Facial Expression Based Music Recommendation System using Deep Learning -- Chapter 4: Exploring Time Series Analysis Techniques for Sales Forecasting -- Chapter 5: Keystroke Dynamics Based Analysis and Classification of Hand Posture using Machine Learning Techniques -- Chapter 6: Teenager Friendly News Classification Using Machine Learning Model -- Chapter 7: Turbulent Particle Swarm Optimization and Genetic Algorithm for Function Maximization -- Chapter 8: An Innovative New Open Computer Vision Framework via Artificial Intelligence with Python -- Chapter 9: Meat Freshness State Prediction using a Novel Fifteen Layered Deep Convolutional Neural Network -- Chapter 10: Object Detection in Autonomous Maritime Vehicles: Comparison between YOLO V8 and EfficientDet. etc.
520 _aThis book includes research papers presented at the International Conference on Data Science and Network Engineering (ICDSNE 2023) organized by the Department of Computer Science and Engineering, National Institute of Technology Agartala, Tripura, India, during July 21–22, 2023. It includes research works from researchers, academicians, business executives, and industry professionals for solving real-life problems by using the advancements and applications of data science and network engineering. This book covers many advanced topics, such as artificial intelligence (AI), machine learning (ML), deep learning (DL), computer networks, blockchain, security and privacy, Internet of things (IoT), cloud computing, big data, supply chain management, and many more. Different sections of this book are highly beneficial for the researchers, who are working in the field of data science and network engineering.
650 0 _aTelecommunication.
650 0 _aArtificial intelligence
_xData processing.
650 0 _aArtificial intelligence.
_958441
650 0 _aInternet of things.
_958845
650 0 _aCooperating objects (Computer systems).
_964303
650 1 4 _aCommunications Engineering, Networks.
650 2 4 _aData Science.
650 2 4 _aArtificial Intelligence.
_958441
650 2 4 _aInternet of Things.
_958845
650 2 4 _aCyber-Physical Systems.
_965638
700 1 _aNamasudra, Suyel.
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700 1 _aTrivedi, Munesh Chandra.
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700 1 _aCrespo, Ruben Gonzalez.
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700 1 _aLorenz, Pascal.
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773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
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776 0 8 _iPrinted edition:
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830 0 _aLecture Notes in Networks and Systems,
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856 4 0 _uhttps://doi.org/10.1007/978-981-99-6755-1
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