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000797911 019__ $$a999653756$$a1000028273$$a1003253767$$a1003506510
000797911 020__ $$a9783319616575$$q(electronic book)
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000797911 24500 $$aDeep learning for biometrics /$$cBir Bhanu, Ajay Kumar, editors.
000797911 260__ $$aCham :$$bSpringer,$$c2017.
000797911 300__ $$a1 online resource (329 pages)
000797911 336__ $$atext$$btxt$$2rdacontent
000797911 337__ $$acomputer$$bc$$2rdamedia
000797911 338__ $$aonline resource$$bcr$$2rdacarrier
000797911 4901_ $$aAdvances in Computer Vision and Pattern Recognition
000797911 5050_ $$aPreface; Outline of the Book and Chapter Synopsis; Challenges for the Future; Acknowledgements; Contents; List of Figures; List of Tables; Deep Learning for Face Biometrics; 1 The Functional Neuroanatomy of Face Processing: Insights from Neuroimaging and Implications for Deep Learning; 1.1 The Functional Characteristics and Organization of the Ventral Face Network in the Human Brain; 1.1.1 Functional Characteristics of the Ventral Face Network; 1.2 The Neural Architecture and Connections of the Ventral Face Network
000797911 5058_ $$a1.2.1 The Functional Organization of the Face Network Is Consistent Across Participants1.2.2 The Cytoarchitecture of Face-Selective Regions; 1.2.3 White Matter Connections of the Ventral Face Network; 1.3 Computations by Population Receptive Fields in the Ventral Face Network; 1.3.1 pRF Measurements Reveal a Hierarchical Organization of the Face Network; 1.3.2 Attention Modulates pRF Properties, Enhancing Peripheral Representations Where Visual Acuity Is the Worst; 1.4 Eyes to the Future: Computational Insights from Anatomical and Functional Features of the Face Network
000797911 5058_ $$a1.4.1 What Is the Computational Utility of the Organized Structure of the Cortical Face Network?1.4.2 What Can Deep Convolutional Networks Inform About Computational Strategies of the Brain?; 1.5 Conclusions; References; 2 Real-Time Face Identification via Multi-convolutional Neural Network and Boosted Hashing Forest; 2.1 Introduction; 2.2 Related Work; 2.3 CNHF with Multiple Convolution CNN; 2.4 Learning Face Representation via Boosted Hashing Forest; 2.4.1 Boosted SSC, Forest Hashing and Boosted Hashing Forest; 2.4.2 BHF: Objective-Driven Recurrent Coding
000797911 5058_ $$a2.4.3 BHF: Learning Elementary Projection via RANSAC Algorithm2.4.4 BHF: Boosted Hashing Forest; 2.4.5 BHF: Hashing Forest as a Metric Space; 2.4.6 BHF: Objective Function for Face Verification and Identification; 2.4.7 BHF Implementation for Learning Face Representation; 2.5 Experiments; 2.5.1 Methodology: Learning and Testing CNHF; 2.5.2 Hamming Embedding: CNHL Versus CNN, BHF Versus Boosted SSC; 2.5.3 CNHF: Performance w.r.t. Depth of Trees; 2.5.4 CNHL and CNHF Versus Best Methods on LFW; 2.6 Conclusion and Discussion; References
000797911 5058_ $$a3 CMS-RCNN: Contextual Multi-Scale Region-Based CNN for Unconstrained Face Detection3.1 Introduction; 3.2 Related Work; 3.3 Background in Deep Convolution Nets; 3.3.1 Region-Based Convolution Neural Networks; 3.3.2 Limitations of Faster R-CNN; 3.3.3 Other Face Detection Method Limitations; 3.4 Contextual Multi-Scale R-CNN; 3.4.1 Identifying Tiny Faces; 3.4.2 Integrating Body Context; 3.4.3 Information Fusion; 3.4.4 Implementation Details; 3.5 Experiments; 3.5.1 Experiments on WIDER FACE Dataset; 3.5.2 Experiments on FDDB Face Database; 3.6 Conclusion and Future Work; References; Deep Learning for Fingerprint, Fingervein and Iris Recognition.
000797911 506__ $$aAccess limited to authorized users.
000797911 588__ $$aDescription based on print version record.
000797911 650_0 $$aBiometric identification.
000797911 650_0 $$aMachine learning.
000797911 7001_ $$aBhanu, Bir.
000797911 7001_ $$aKumar, Ajay.
000797911 77608 $$iPrint version:$$aBhanu, Bir$$tDeep Learning for Biometrics$$dCham : Springer International Publishing,c2017$$z9783319616568
000797911 830_0 $$aAdvances in computer vision and pattern recognition.
000797911 852__ $$bebk
000797911 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-61657-5$$zOnline Access$$91397441.1
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