Deep Learning for Biometrics
This timely text/reference presents a broad overview of advanced deep learning architectures for learning effective feature representation for perceptual and biometrics-related tasks. The text offers a showcase of cutting-edge research on the use of convolutional neural networks (CNN) in face, iris,...
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| Other Authors: | , |
| Format: | Electronic eBook |
| Language: | English |
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Cham :
Springer International Publishing : Imprint: Springer,
2017.
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| Series: | Advances in Computer Vision and Pattern Recognition,
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| Subjects: | |
| Online Access: | Full Text via HEAL-Link |
Table of Contents:
- 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.
