Advances in Artificial Intelligence and Machine Learning in Big Data Processing

Second International Conference, AAIMB 2024, Chennai, India, December 12–13, 2024, Proceedings, Part I

AvGeetha Ramachandran,Nhu-Ngoc Dao

Häftad, Engelska, 2026

Del i serien Communications in Computer and Information Science

1 110 kr

Beställningsvara. Skickas inom 10-15 vardagar. Fri frakt över 249 kr.

Beskrivning

This two-set volume CCIS 2653 and 2654 constitutes the refereed proceedings of the Second International Conference on Advances in Artificial Intelligence and Machine Learning in Big Data Processing, AAIMB 2024, held in Chennai, India, during December 12–13, 2024.The 59 full papers included in this book were carefully reviewed and selected from 434 submissions. The papers are organized in the following topical sections:Part I: artificial intelligence and data analytics; machine learning.Part II: artificial intelligence and data analytics; deep learning.

Produktinformation

Utgivningsdatum:2026-01-10
Mått:155 x 235 x 25 mm
Vikt:680 g
Format:Häftad
Språk:Engelska
Serie:Communications in Computer and Information Science
Antal sidor:436
Förlag:Springer Nature Switzerland AG
ISBN:9783032130259

Utforska kategorier

Databaser inom Data och IT
Systemvetenskap och AI inom Data och IT

Innehållsförteckning

.- ARTIFICIAL INTELLIGENCE & DATA ANALYTICS..- Agent-Based Flood Evacuation Modeling: Optimizing Transportation, Shelter Allocation and Traffic Control..- PhysioAI - Smart physiotherapy solutions driven by AI technology..- Predictive Modelling For Network Threat Detection Using Artificial Intelligence..- Enhancing Generative AI with Retrieval-Augmented Generation : A Comparative Study..- AI-Based tool for preliminary diagnosis of Dermatological..- Integrating Artificial Intelligence and Machine Learning in Indian Manufacturing Industries: Pathways to Sustainable Growth..- Multimodal Mental Health Chatbot..- Leveraging Generative AI in Management Decision Making: Opportunities and Challenges..- Hybrid Contextual Embeddings with Attention Mechanisms for Enhanced Sentiment Analysis in COVID-19 Tweets..- A Major Role of Artificial Intelligence in Modern Healthcare..- Adopting AIML for Marketing of SME's..- Smart Recipe Using Gen-AI with BMI and Vegetables Detection..- MACHINE LEARNING..- Personality Prediction Machine Learning Model Using XGBoost To Facilitate Interpersonal Relationships..- Enhancing Emotion Detection Classification through Bagging Techniques..- Assistive Technology to Translate Hand Gestures to Text Using Lenet and Alexnet..- Analysis of Breast Cancer Detection with Gradient Boosted Tree using Rapid Miner..- Epileptical Seizure Classification from Electroencephalography Signals and 2-D Images: A Comprehensive Approach..- Evaluating Machine Learning Algorithms for Breast Cancer Detection: Logistic Regression, Naive Bayes, and Decision Tree Models..- Comparative Evaluation of Machine Learning Methods for Enhanced Intrusion Detection..- Combining Principal Component Analysis Method and Artificial Neural Network Model for Surface Ozone Concentration Prediction in Baghdad, Iraq..- Speech Emotions Recognition Using Machine Learning..- Enhancement of Misdeed Node Catching and Fast Transmission in Delay Tolerance Network using 5G Technology..- Adaptive Traffic Control System using Machine Learning..- Enhanced Food Inflation Forecasting: An Implementation Analysis of Decision Tree Forest and Random Forest Algorithms..- Exploring the various Machine Learning Models for Image Generation - A Comprehensive Survey Unlocking the Future of Digital Creativity..- Frenet-RRT-Cartesian with Machine Learning: An Integrated Algorithm for Optimized Navigation of Autonomous Vehicles in Urban Environments..- Autoscaling In Cloud Computing With Ann And Linear Regression For Model Complexity Reduction..- Scalable Dog Breed Classification With YOLO and EfficientNet-B0: Enhancing Accuracy and Speed through High-Performance Computing..- Impact of Financial modelling on adaptability of AI & ML in Indian Manufacturing MSME's..- SilkwormCocoonsQualityAssessmentandClassificationusingOptimizedResidual GraphConvolutionalNeuralNetwork.