Computation of Artificial Intelligence and Machine Learning: First International Conference, ICCAIML 2024, Jaipur, India, January 18-19, 2024, Proceedings, Part I

by Amit Kumar Bairwa (Editor), Varun Tiwari (Editor), Santosh Kumar Vishwakarma (Editor), Milan Tuba (Editor), Thittaporn Ganokratanaa (Editor)

Overview

The two-volume set, CCIS 2184-2185, constitutes the refereed proceedings of the First International Conference on Computation of Artificial Intelligence and Machine Learning, ICCAIML 2024, held in Jaipur, India, in January 18–19, 2024.

The 60 papers included in these volumes were carefully reviewed and selected from 645 submissions. These papers focus on various subject areas within the field of Artificial Intelligence and Machine Learning, such as Neural Networks and Deep Learning, Natural Language Processing, Computer Vision, Reinforcement Learning, Data Mining and Big Data Analytics, AI in Healthcare and Biomedical Applications, Autonomous Systems and Robotics, AI Ethics and Fairness, AI in Finance and Eco-nomics.

Product Details

ISBN-13:	9783031714801
Publisher:	Springer Nature Switzerland
Publication date:	10/23/2024
Series:	Communications in Computer and Information Science , #2184
Edition description:	2024
Pages:	399
Product dimensions:	6.10(w) x 9.25(h) x (d)

Table of Contents

.- Machine learning applications in the diagnosis of leukemia: Current trends and future directions.

.- Intelligent Conversational Chatbots: Design Approaches & Techniques.

.- Intelligent Conversational Chatbots: History, Taxonomy, Classification with PRISMA Model.

.- Unleashing the Power of Dynamic Mode Decomposition and Deep Learning for Rainfall Prediction in North-East India.

.- Patient’s Condition Categorization Using Drug Reviews.

.- Systematic Review on Sustainable Healthcare Practices: A Bibliometric Approach.

.- Violence Detection through Deep Learning model in Surveillance.

.- Role of ChatGpt in Decision Making Across Industries: An Indian Perspective.

.- Identification of Splice Image Forgeries with Enhanced DenseNet201 and VGG19.

.- Identification of DR (Diabetic Retinopathy) from Messidor-2 Dataset Images using Various Deep and Machine Learning Techniques: A Comparative Analysis.

.- Access- Based Authentication of Health care Record in Block Chain: A Survey from Security Perspective.

.- Smart Entry Management using IoT and Number Plate Recognition for Organizational Security.

.- Enhancing Player Engagement through Gesture- Based Interactions in Tic-Tac-Toe.

.- Aggressive Bangla Text Detection Using Machine Learning and Deep Learning Algorithms.

.- A Comparative Evaluation of Machine Learning Techniques for Detecting Malicious Network Traffic.

.- Enhancing Cyclone Intensity Prediction through Deep Learning Analysis of Imagery Datasets.

.- Revolutionizing Road Safety: Machine Learning Approaches for Predicting Road Accident Severity.

.- Survey and Analysis of Machine Learning Methods for Parkinson's Disease Diagnosis .

.- Accelerated GPU-based Clustering, Classification and Regression using RAPIDS: A Comparative Study.

.- Talk to Hands: A Sign Language Solution for Speech Impaired People.

.- Deep Learning-Based Thyroid Cancer Detection and Segmentation Using Convolutional Neural Networks.

.- Early Autism Spectrum Disorder Prediction using Fine-Tuned Bernoulli’s Naive Bayes Algorithm.

.- Heart Disease prediction model using machine learning techniques.

.- A review to enhance driving behavior through advanced drowsiness detection systems: Integrating deep learning and machine learning techniques.

.- Advancing Peer Review Integrity: Automated Reviewer Assignment Techniques with a Focus on Deep Learning Applications.

.- Automated Potato Disease Classification Using Deep Learning- A Comparative Analysis of Convolutional Neural Networks.

.- Enhancing Monkeypox Disease Detection Using Image Processing and Deep Learning.

.- Deep Learning Based Tomato Leaf Disease Prediction Approach.

.- Predicting Sk Market Trends: Machine Learning Approaches of a possible uptrend or downtrend.

.- A scientific classification-based survey of Intrusion Detection System using Machine Learning Approach.