Titlebook: Biometric Recognition; 12th Chinese Confere Jie Zhou,Yunhong Wang,Shiqi Yu Conference proceedings 2017 Springer International Publishing AG

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Ursula Lanvers,Amy S. Thompson,Martin Eastow and expensive. An effective approach to reduce the annotation effort is active learning (AL). However, the traditional AL methods are limited by the hand-craft features and the small-scale datasets. In this paper, we propose a novel deep active learning framework combining the optimal feature rep

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neolith

Bone-Scan

ostracize

Charlotte R. Hancock,Kristin J. Davingerprint features, pore-scale facial features are one of the biometric features that can distinguish human identities. Most of the local features of biometric depend on hand-crafted design. However, such hand-crafted features rely heavily on human experience and are usually composed of complicated o

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CRACY

Sílvia Melo-Pfeifer,Mara Thölkesfeatures to obtain better face representation and introduce block loss to enable our model to be robust to occluded faces. Then we adopt WR-Inception network with shallower and wider layers as our base feature extractor. Finally, we apply a new pre-training strategy to learn representation more suit

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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/188174.jpg

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