Author

A. Beitollahi

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Open access Aug 2026

Deep Learning Framework for Financial Fraud Detection: Systematic Feature Engineering and Comparative Evaluation of Neural Architectures

Three deep tabular models, namely, an advanced multilayer perceptron (AdvancedMLP), an attention‐based residual network (AttentionFraudNet), and an advanced residual network (AdvancedResNet), are compared against three traditional machine learning baselines, including Random Forest, Gradient Boosting, and Logistic Regression.

Vahid Azarvand, Parvin Azhdari, A. Beitollahi · Engineering Reports · 0 citations