Titlebook: Biometric Recognition; 14th Chinese Confere Zhenan Sun,Ran He,Zhenhua Guo Conference proceedings 2019 Springer Nature Switzerland AG 2019 a

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Fingerprint Presentation Attack Detection via Analyzing Fingerprint Pairsll use of the difference in materials between the fake fingerprint and the real fingerprint, we proposed to utilize two images of a finger for classification. A pair of fingerprints are first aligned using a deformable registration algorithm and then are fed into MobileNet-v2 networks to perform the

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Finger Vein Recognition Based on Double-Orientation Coding Histogramin recognition has great research significance. In the paper, we offer a double orientation coding (DOC) method for finger vein recognition to represent the direction of vein texture using two orientation values. To strengthen the discrimination ability and robustness of the direction description, w

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Fingerprint Classification Based on Lightweight Neural Networksn model has many problems such as complicated operation, lots of parameters, massive data. In this paper, we present a lightweight neural network for automatic extraction features and classification of fingerprint images. Fingerprint Region of Interest (ROI) images is regarded as the input of the ne

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A Novel Method for Finger Vein Recognitionve shown a good performance. However, these systems usually adopt such large networks or complex step-by-step processes that they cannot be applied to the hardware platform with limited computing power and small memory. To address this limitation, this research proposes a finger vein recognition net

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Global and Local Spatial-Attention Network for Isolated Gesture Recognitionnformation from multi-modality inputs. To this end, we propose a novel attention-based method with 3D convolutional neural network (CNN) to recognize isolated gesture recognition. It includes two parts. The first one is a global and local spatial-attention network (GLSANet), which takes into account

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