Titlebook: Deep Learning for Biometrics; Bir Bhanu,Ajay Kumar Book 2017 Springer International Publishing AG, part of Springer Nature 2017 Deep Learn

离开浮于空中

书目名称Deep Learning for Biometrics影响因子(影响力)




书目名称Deep Learning for Biometrics影响因子(影响力)学科排名




书目名称Deep Learning for Biometrics网络公开度




书目名称Deep Learning for Biometrics网络公开度学科排名




书目名称Deep Learning for Biometrics被引频次




书目名称Deep Learning for Biometrics被引频次学科排名




书目名称Deep Learning for Biometrics年度引用




书目名称Deep Learning for Biometrics年度引用学科排名




书目名称Deep Learning for Biometrics读者反馈




书目名称Deep Learning for Biometrics读者反馈学科排名

AMPLE

辞职

CMS-RCNN: Contextual Multi-Scale Region-Based CNN for Unconstrained Face Detectionacial periocular recognition, facial landmarking and pose estimation, facial expression recognition, 3D facial model construction, etc. Although the face detection problem has been intensely studied for decades with various commercial applications, it still meets problems in some real-world scenario

道学气

Latent Fingerprint Image Segmentation Using Deep Neural NetworkRBMs), and uses it to perform segmentation of latent fingerprint images. Artificial neural networks (ANN) are biologically inspired architectures that produce hierarchies of maps through learned weights or filters. Latent fingerprints are fingerprint impressions unintentionally left on surfaces at a

TEN

Finger Vein Identification Using Convolutional Neural Network and Supervised Discrete Hashingnal privacy and anonymity in during the identification process. The Convolutional Neural Network (CNN) has shown remarkable capability for learning biometric features that can offer robust and accurate matching. We introduce a new approach for the finger vein authentication using the CNN and supervi

IRATE

IRATE

纤细

genuine

几何学家