Data Science and Network Engineering : Proceedings of ICDSNE 2023

個数:1
紙書籍版価格
¥55,964
  • 電子書籍

Data Science and Network Engineering : Proceedings of ICDSNE 2023

  • 言語:ENG
  • ISBN:9789819967544
  • eISBN:9789819967551

ファイル: /

Description

This 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.

Table of Contents

Part 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.

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