The Use of Attention-RNN and Dense Layer Combinations and The Performance Metrics Achieved in Palm Vein Recognition - Indriani, Indriani; Syukriyah, Yenie (Universitas Ahmad Dahlan, 2025)
The utilization of palm veins in vascular biometrics is widely recognized, offering significant potential and challenges for advancing individual recognition technology. Deep learning has played a crucial role in enhancing the accuracy of these recognition systems. In this study, we proposed combining Attention-RNN and Dense Layer. To validate this proposed method, three deep learning model scenarios were implemented: (1) a combined Dense Layer with RNN, (2) an Attention-RNN model, and (3) a combined Attention-RNN with a Dense Layer for palm vein recognition. Experimental results demonstrated that the Attention-RNN combined with the Dense Layer achieved the highest accuracy, outperforming the other two models. The model’s performance was evaluated on two datasets, achieving 95% accuracy on the Kaggle dataset and 83% on the CASIA dataset, confirming its effectiveness in palm vein recognition.