Puzzle Zeitvertreib Beste 4K Filme Beste Multimedia-Lernspiele % SALE %

Deep Learning for Biometrics


Deep Learning for Biometrics
111.11 CHF
Versandkostenfrei

Versandkostenfreie Lieferung!

Lieferzeit: 7-14 Werktage

  • 10471626


Beschreibung

Part I: Deep Learning for Face Biometrics

The Functional Neuroanatomy of Face Processing: Insights from Neuroimaging and Implications for Deep Learning
Kalanit Grill-Spector, Kendrick Kay and Kevin S. Weiner

Real-Time Face Identification via Multi-Convolutional Neural Network and Boosted Hashing Forest
Yuri Vizilter, Vladimir Gorbatsevich, Andrey Vorotnikov and Nikita Kostromov

CMS-RCNN: Contextual Multi-Scale Region-Based CNN for Unconstrained Face Detection
Chenchen Zhu, Yutong Zheng, Khoa Luu and Marios Savvides

Part II: Deep Learning for Fingerprint, Fingervein and Iris Recognition

Latent Fingerprint Image Segmentation Using Deep Neural Networks
Jude Ezeobiejesi and Bir Bhanu

Finger Vein Identification Using Convolutional Neural Network and Supervised Discrete Hashing
Cihui Xie and Ajay Kumar

Iris Segmentation Using Fully Convolutional Encoder-Decoder Networks
Ehsaneddin Jalilian and Andreas Uhl

Part III: Deep Learning for Soft Biometrics

Two-Stream CNNs for Gesture-Based Verification and Identification: Learning User Style
Jonathan Wu, Jiawei Chen, Prakash Ishwar and Janusz Konrad

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)
Felix Juefei-Xu, Eshan Verma and Marios Savvides

Gender Classification from NIR Iris Images Using Deep Learning
Juan Tapia and Carlos Aravena

Deep Learning for Tattoo Recognition
Xing Di and Vishal M. Patel

Part IV: Deep Learning for Biometric Security and Protection

Learning Representations for Cryptographic Hash Based Face Template Protection
Rohit Kumar Pandey, Yingbo Zhou, Bhargava Urala Kota and Venu Govindaraju

Deep Triplet Embedding Representations for Liveness Detection
Federico Pala and Bir Bhanu

Eigenschaften

Breite: 187
Gewicht: 644 g
Höhe: 234
Länge: 14
Seiten: 312
Sprachen: Englisch
Autor: Ajay Kumar, Bir Bhanu

Bewertung

Bewertungen werden nach Überprüfung freigeschaltet.

Die mit einem * markierten Felder sind Pflichtfelder.

Ich habe die Datenschutzbestimmungen zur Kenntnis genommen.

Zuletzt angesehen

eUniverse.ch - zur Startseite wechseln © 2021 Nova Online Media Retailing GmbH