Deep Learning for Biometrics

Häftad, Engelska, 2018

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Issues of biometrics security are also examined. Topics and features: addresses the application of deep learning to enhance the performance of biometrics identification across a wide range of different biometrics modalities;

Produktinformation

Utgivningsdatum2018-05-12
Mått155 x 235 x undefined mm
FormatHäftad
SpråkEngelska
SerieAdvances in Computer Vision and Pattern Recognition
Antal sidor312
FörlagSpringer International Publishing AG
ISBN9783319871288

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Dr. Bir Bhanu is Bourns Presidential Chair, Distinguished Professor of Electrical and Computer Engineering and the Director of the Center for Research in Intelligent Systems at the University of California at Riverside, USA. Some of his other Springer publications include the titles Video Bioinformatics, Distributed Video Sensor Networks, and Human Recognition at a Distance in Video. Dr. Ajay Kumar is an Associate Professor in the Department of Computing at the Hong Kong Polytechnic University.

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.