Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Credit Card Fraud Detection System Using Deep Learning Techniques

Credit Card Fraud Detection System Using Deep Learning Techniques

Baghsawari, Megha

Paperback

General Computers

ISBN10: 6209892256
ISBN13: 9786209892257
Publisher: LAP Lambert Academic Publishing
Published: Apr 17 2026
Pages: 104
Weight: 0.33
Height: 0.25 Width: 6.00 Depth: 9.00
Language: English
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.

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