Biometric Verification

Biometric verification uses unique human traits for authentication, aiming to improve security and convenience over traditional methods. Current research emphasizes enhancing accuracy and robustness through multi-biometric approaches (combining traits like face, iris, and voice), advanced deep learning architectures such as Siamese and Vision Transformer networks, and improved liveness detection to counter spoofing attacks. Addressing inherent biases in biometric systems across demographic groups and developing efficient, privacy-preserving methods are also key focuses, with ongoing efforts to improve explainability and reduce computational demands for wider applicability.