Traditional Authentication System

Traditional authentication systems, aiming to securely verify identities, are undergoing significant transformation driven by advancements in machine learning. Current research focuses on developing more robust and reliable biometric systems using diverse modalities like eye movements, muzzle prints, and even handwritten passwords, often employing deep learning architectures such as ResNet, VGG, U-Net, and YOLO for improved accuracy and efficiency. This shift towards biometric authentication offers enhanced security and convenience compared to traditional methods, impacting various fields from animal identification and ecological research to access control and anti-counterfeiting measures.