Advanced Network Technologies and Intelligent Computing: Third International Conference, ANTIC 2023, Varanasi, India, December 20-22, 2023, Proceedings, Part IV

Author:   Anshul Verma ,  Pradeepika Verma ,  Kiran Kumar Pattanaik ,  Sanjay Kumar Dhurandher
Publisher:   Springer International Publishing AG
Edition:   2024 ed.
Volume:   2093
ISBN:  

9783031640667


Pages:   382
Publication Date:   26 July 2024
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Advanced Network Technologies and Intelligent Computing: Third International Conference, ANTIC 2023, Varanasi, India, December 20-22, 2023, Proceedings, Part IV


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Overview

The 4-volume proceedings set CCIS 2090, 2091,2092 and 2093 constitute the refereed post-conference proceedings of the Third International Conference on Advanced Network Technologies and Intelligent Computing, ANTIC 2023, held in Varanasi, India, during December 20-22, 2023. The 87 full papers and 11 short papers included in this book were carefully reviewed and selected from 487 submissions. The conference papers are organized in topical sections on:  Part I - Advanced Network Technologies. Part II - Advanced Network Technologies; Intelligent Computing. Part III - IV - Intelligent Computing.  

Full Product Details

Author:   Anshul Verma ,  Pradeepika Verma ,  Kiran Kumar Pattanaik ,  Sanjay Kumar Dhurandher
Publisher:   Springer International Publishing AG
Imprint:   Springer International Publishing AG
Edition:   2024 ed.
Volume:   2093
ISBN:  

9783031640667


ISBN 10:   3031640667
Pages:   382
Publication Date:   26 July 2024
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

.- Intelligent Computing.  .- Neural Network Approach for Early detection of Sugarcane Diseases. .- Enhanced Residual Network Framework for Robust Classification of Noisy Lung Cancer CT Images. .- Single-Cell Drug Perturbation Prediction Using Machine Learning. .- Underwater Image Enhancement using Convolutional Neural Network and the MultiUnet Model. .- A hybrid time series model for the spatio-temporal analysis of air pollution prediction based on PM2.5. .- Detection of Lung Diseases Using Deep Transfer Learning-Based Convolution Neural Networks. .- DG-GAN: A Deep Neural Network for Real-World Anomaly Detection in Surveillance Videos. .- Auto-LVEF: A novel method to determine Ejection Fraction from 2D echocardiograms. .- Phishing Detection in Browser-In-The-Middle: A Novel Empirical Approach Incorporating Machine Learning Algorithms. .- Feature Engineering for Predicting Consumer Purchase Behavior: A Comprehensive Analysis. .- Enhanced Simulation of Collision Events Using Quantum GANs for Jet Images Generation. .- Class imbalance learning using Fuzzy SVM with Fuzzy Weighted Gaussian Kernel. .- Material Handling Cost (MHC) Minimization through Facility Layout Design (FLD) Using Genetic Algorithm (GA) combined with the Particle Swarm Optimization (PSO) Method. .- Detecting ADHD among children using EEG signals. .- Enhancing Skin Cancer Classification with Ensemble Models. .- Efficient real-time Sign Detection for Autonomous Vehical in Hazy environment using Deep Learning Models. .- Kannada Continuous Speech Recognition using Deep Learning. .- A new type of classification algorithm inspired by the chromatographic separation mechanism. .- Comparative Analysis of ELM and Sparse Bayesian ELM for Healthcare Diagnosis. .- Integration of Generative AI and Deep Tabular Data Learning Architecture for Heart Attack Prediction. .- Navigating the Domain Shift: Object Detection in Indian Road Datasets with Limited Data. .- An Efficient Hybrid Algorithm with Novel Inver-over Operator and Ant Colony Optimization for Traveling Salesman Problem. .- Sparsity Analysis of New Biased Pearson Similarity Measure for Memory Based Collaborative Filtering. .- Advancing Medical Predictive Models with Integrated Approaches.

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