Biometric Model

Biometric models aim to automatically identify individuals based on unique physiological or behavioral traits, with applications ranging from security systems to personalized devices. Current research focuses on improving model accuracy and robustness across diverse demographics and image qualities, exploring architectures like deep neural networks and generative adversarial networks (GANs) for various biometric modalities (fingerprints, irises, face, body shape, and even mouse dynamics). A key challenge is mitigating biases and vulnerabilities, including attacks that exploit model weaknesses or generate synthetic biometric data, while also addressing privacy concerns related to data collection and model inversion.