Credit Card Fraud Detection System Using Deep Learning Techniques

By: Megha Baghsawari

Credit card fraud detection remains a significant challenge due to the growing complexity of fraudulent behaviour and the severe class imbalance in transaction data. This study presents a hybrid deep learning approach that combines three advanced models-an Artificial Neural Network (ANN) enhanced with Batch Normalization and Dropout, along with VGG16 and VGG19 architectures-to enhance detection accuracy and reliability. The system begins with extensive data pre-processing, including Standard Scaling for normalization, Synthetic Minority Over-sampling Technique (SMOTE) to balance class distribution, and Principal Component Analysis (PCA) for dimensionality reduction.

• Format: Paperback
• Language: English
• ISBN: 6209892256
• ISBN13: 9786209892257
• Release Date: April 2026
• Publisher: LAP Lambert Academic Publishing
• Length: 104 Pages
• Weight: 0.34 lbs.
• Dimensions: 9.0" x 0.3" x 6.0"