Small Area Fingerprint

Small-area fingerprint recognition focuses on improving biometric authentication using fingerprints captured from small sensors, often found in mobile devices. Current research emphasizes developing robust deep learning models, such as convolutional autoencoders and multi-task neural networks, to address challenges like noise (especially from wet fingerprints) and limited data availability. These advancements aim to enhance the accuracy and reliability of fingerprint-based security systems in compact devices, impacting areas like mobile phone security and digital payments.