Advances in Artificial Intelligence and Machine Learning in Big Data Processing

First International Conference, AAIMB 2023, Chennai, India, August 17-18, 2023, Proceedings, Part-I
2025
ISBN: 978-3-031-73064-1
Verlag: Springer Nature Switzerland

Buch, Englisch, Band 2202, 331 Seiten, Format (B × H): 155 mm x 235 mm, Gewicht: 534 g

Reihe: Communications in Computer and Information Science

This book constitutes the refereed proceedings of the First International Conference on Advances in Artificial Intelligence & Machine Learning in Big Data Processing, AAIMB 2023, held in Chennai, India, during August 17–18, 2023.

The 51 full papers presented were carefully reviewed and selected from 183 submissions. They were organized in the following topical sections: 

Part I- artificial intelligence and data analytics; deep learning.

Part II- artificial intelligence and data analytics; machine learning.

Zielgruppe

Research

Autoren/Hrsg.

Geetha, R.

Khalid, Saeed

Dao, Nhu-Ngoc

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken Data Mining
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Wissensbasierte Systeme, Expertensysteme

Inhaltsverzeichnis

.- Artificial Intelligence and Data Analytics.

.- A Novel Revolutionizing Medical Surgery Procedures Using Mixed Reality.

.- Data Mining-based Classification Algorithms for Predicting Mental Health.

.- Topological Navigation of Path Planning Using a Hybrid Architecture in Wheeled Mobile Robot.

.- Abnormal Behaviour Detection in Surveillance Videos.

.- ISAApp – Image based Smart Attendance Application.

.- A Self-Learning AI-based Information Leak Protection System.

.- Deep Learning.

.- Enhancing Abnormal Object Detection in Camera Based Systems through Computer Vision and Deep Learning Techniques.

.- Detection and Classification of Brain Tumor in Magnetic Resonance Images Using CNN.

.- Diagnosis of Parkinson’s disease using Machine Learning and Deep Learning Techniques.

.- A Survey on Deep Learning Based Human Activity Recognition System.

.- A Deep Learning Approach for Non - Invasive Body Mass Index Calculation.

.- Early-Stage Detection of Alzheimer’s Disease Using MRI Scans with Deep Learning.

.- Penguin Search Optimization with Deep Learning based Cybersecurity Malware Spectrogram Image Classification.

.- Detection and Classification of Skin Disease Using CNN.

.- Estimation of Above Ground Biomass Using Machine Learning and Deep Learning Algorithms: A Review.

.- URL Phishing Detection using Deep Learning and Machine Learning Techniques.

.- Enhanced Disease Recognition and Classification in Black Gram Plant Leaves using Deep learning.

.- Ensemble Deep Learning Approach for Identification of DDOS Attack.

.- ROCLT : Enhanced Text classifier for Sentiment on Imbalanced Multiclass Tweet Data using Hybrid Deep Learning Techniques.

.- Computer Vision to Animal Footprint Classification Based on Deep Learning Model.

.- Speech Emotion Recognition Using CNN Classifier Based on Deep Learning Model.

.- Face Detection and Recognition for Criminal Identification System using Deep Learning.

.- Automated Essay Grading System for IELTS using Bi-LSTM.

.- Automized Quick Prediction of Skin Cancer Diagnosis by Enhanced Deep Convolutional Neural Network.

.- Clustering based Demand Prediction using Long ShortTerm Memory (LSTM) in Retail Supply Chains.

.- Early Detection of Diabetic Retinopathy using Deep Convolutional Neural Network.