Advances in Artificial Intelligence and Machine Learning in Big Data Processing by Geetha, R.; Dao, Nhu-Ngoc; Khalid, Saeed;

Hosszú leírás:

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.

Tartalomjegyzék:

.- Artificial Intelligence and Data Analytics.

.- Feature Fusion Based Bayesian model detection in the prognosis of glioma - A Survey.

.- AI Voice Assistant Using Python.

.- Research Output on Artificial Intelligence in India: A Scientometric study.

.- Analyzing Hand Gestures using Object Detection and Processing it into Local Language.

.- A Review of an Automated Model for Sexist Language Detection and Replacement of Sexist Terms.

.- Machine Learning.

.- Detection of DoS Attack using Machine learning in Software Defined Network.

.- Regression Model Approach towards Concrete Compressive Strength Prediction and Evaluation.

.- An Enhanced Artificial Neural Network Model for type 2 Diabetes Classification 84 using SMOTE and SMOTETomek with Effective Feature Selection Methods.

.- Machine Learning based Traffic Congestion and Accident Prevention Analysis.

.- A Comparative Evaluation of Machine Learning Methods for Predicting Chronic Kidney Disease.

.- Detecting Implicit Aspects of Customer Experience in the Hotel Industry Using a Machine Learning Algorithm.

.- Vehicle Insurance Claim Prediction.

.- Ensemble Learning Models for Detecting Spam Over Social Networks Using RFE.

.- An Intelligent Machine Learning Framework for Melanoma Classification System: A Critique.

.- Online Network Intrusion Detection System for IOT structure using Machine Learning Techniques.

.- An Analysis of Machine Learning Tools and Algorithms.

.- Ensemble Learning-Based Android Malware Detection.

.- Handling Imbalanced Data for Credit Card Fraudulent Detection: A Machine Learning Approach.

.- An Enhanced Learning Model Based on an Improved Random Forest Classifier and an Integrated
Attribute Selector for Healthcare Datasets.

.- Engineering Open Access Research Analysis of Machine Learning Publications in India.

.- Optimizing Coronary Illness Prediction Using Hyperparameter Tuning Through Machine Learning.

.- Detection and Classification of Intracranial Tumor in Machine Learning using Fuzzy C-Means Algorithm.

.- A survey of Anomaly Detection in Video Surveillance.

.- Prediction and comparison of ML Algorithm for Heart Disease.

.- Comparative Analysis of Classifiers for Chat Classification: A Study on Random Forest, Support
Vector Machine and Multinomial Naive Bayes with Bag of Words and TF-IDF.