IEEE

Enhanced Predictive Modeling for Anomaly Detection in Financial Transactions Using Machine Learning

Abstract: Credit card fraud detection presents a significant challenge due to the extreme class imbalance in transaction datasets. Traditional machine learning models struggle to achieve high recall ...
Visual Studio Magazine

Anomaly Detection Using K-Means Clustering with JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of anomaly detection using k-means data clustering, implemented with JavaScript. Compared to other anomaly detection techniques, ...
Frontiers

Anomaly detection in netflow traffic: workflow for dataset preparation and analysis

Information and communication technology (ICT) is crucial for maintaining efficient communications, enhancing processes, and enabling digital transformation. As ICT becomes increasingly significant in ...
GitHub

Surpriver - Find High Moving Stocks before they Move

Surpriver - Find High Moving Stocks before they Move Find high moving stocks before they move using anomaly detection and machine learning. Surpriver uses machine learning to look at volume + price ...
Frontiers

HairSentinel: a time-aware anomaly detection framework for forecasting hairfall trends using temporal fusion transformers

1 Analytics Department, School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, Tamil Nadu, India 2 Department of Data Science, School of Computer Science and Engineering ...
IEEE

Machine Learning Model for Road Anomaly Detection Using Smartphone Accelerometer Data

Abstract: This paper presents a vibration-based machine learning approach for road surface monitoring using smartphone sensors. With Mexico’s road network experiencing significant deterioration and ...
Scientific Research Publishing

Hossain, M.A., et al. (2024) Anomaly-Based Threat Detection in Smart Health Using Machine Learning. BMC Medical Informatics and Decision Making, 24, Article No. 347.

ABSTRACT: Generative AI is poised to revolutionize performance engineering by automating key tasks, improving prediction accuracy, and enabling real-time system adaptation. This paper explores the ...