Deep Learning for Biometrics

Part I: Deep Learning for Face Biometrics.- The Functional Neuroanatomy of Face Processing: Insights from Neuroimaging and Implications for Deep Learning.- Real-Time Face Identification via Multi-Convolutional Neural Network and Boosted Hashing Forest.- CMS-RCNN: Contextual Multi-Scale Region-Based CNN for Unconstrained Face Detection.- Part II: Deep Learning for Fingerprint, Fingervein and Iris Recognition.- Latent Fingerprint Image Segmentation Using Deep Neural Networks.- Finger Vein Identification Using Convolutional Neural Network and Supervised Discrete Hashing.- Iris Segmentation Using Fully Convolutional Encoder-Decoder Networks.- Part III: Deep Learning for Soft Biometrics.- Two-Stream CNNs for Gesture-Based Verification and Identification: Learning User Style.- DeepGender2: A Generative Approach Toward Occlusion and Low Resolution Robust Facial Gender Classification via Progressively Trained Attention Shift Convolutional Neural Networks (PTAS-CNN) and Deep Convolutional Generative Adversarial Networks (DCGAN).- Gender Classification from NIR Iris Images Using Deep Learning.- Deep Learning for Tattoo Recognition.- Part IV: Deep Learning for Biometric Security and Protection.- Learning Representations for Cryptographic Hash Based Face Template Protection.- Deep Triplet Embedding Representations for Liveness Detection.

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• Inteligência artificial
• Engenharia electrónica
• Reconhecimento de padrões
• Teoria matemática da computação
• Processamento de sinais

Deep Learning;Face;Fingerprint;Iris;Gait;Template Protection;Anti-Spoofing;Alexnet;CNN;RBM;Biometrics;Human Surveillance