This project presents a robust multimodal biometric authentication system that integrates facial recognition voice verification and fingerprint identification using deep learning techniques. By leveraging convolutional neural networks (CNNs) and advanced fusion strategies the system enhances security accuracy and resilience against spoofing attacks compared to traditional unimodal approaches. Designed for high performance and adaptability the solution demonstrates the potential of deep learning to revolutionize biometric authentication in real-world applications ranging from secure access control to financial services.
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