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This thesis explores the application of deep learning, specifically Convolutional Neural Networks (CNNs), for face recognition in images. It fine-tunes and tests two architectures, AlexNet and VGG19, on various datasets and evaluates verification algorithms, achieving an impressive Area Under the Receiver Operating Characteristic curve of 99.6%. The work demonstrates significant advancements in the accuracy of face recognition systems using state-of-the-art techniques.

Author

sovife1178

Language

EN