biometrics based on deep learning: a survey

Biometrics is concerned with the identification and verification of people using their physiological and behavioral characteristics which are enduring and distinctive and these characteristics can distinguish one person from another. systems for biometric recognition integrate intricate technological, operational, and definitional choices in a variety of scenarios. these systems combined with biometric strategies and authentication techniques will help to enhance the security of applications that rely on user collaboration. they aid in locating a specific person inside a set of industrial networks, office buildings, and control systems. this paper focused on convolutional neural networks, deep learning in biometrics, unimodal and multimodal biometrics, template security, and general challenges of biometrics. this article examines a comprehensive and in-depth survey that succinctly and methodically on fingerprint and vein biometrics, analyzed, and compared to determine which is more effective in verifying the identification of a specific user and to highlight a biometric authentication system and the challenges of biometrics. we discuss each method and dataset used as well as their efficacy. the key difficulties in using these biometric recognition models as well as prospective directions for future study in this area are also covered.