S. Suwarno

Impact of Kernel Size on CNN-Based Fingerprint Gender Classification

This paper presents a straightforward CNN model designed to classify gender based on fingerprints. The model consists of three convolutional layers and a classification layer. To ensure computational efficiency, we select kernel sizes ranging from 3×3 to 8×8. For training, we utilized the NIST (National Institute of St...