Titlebook: Biometric Recognition; 16th Chinese Confere Weihong Deng,Jianjiang Feng,Zhaofeng He Conference proceedings 2022 The Editor(s) (if applicabl

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SP-FVR: SuperPoint-Based Finger Vein Recognitionthe SuperPoint model. Finally, the keypoints are matched by a bilateral strategy. Experiments on the HKPU and SDU-MLA databases demonstrate the effectiveness of the proposed method in real applications, the EERs are 0.0025 and 0.0138, with the FRRs-at-0-FAR of 0.0218 and 0.0890, respectively.

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不怕任性

https://doi.org/10.1057/9780230502666 Among them, finger based multimodal biometric recognition is the most common and efficient way. However, biometric recognition has lots of problems such as too high feature dimensions, high computational complexity and insufficient correlation between modal classes. This paper propose an improved D

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https://doi.org/10.1057/9780230502666k, which may affect the effectiveness of finger vein extraction. In this paper, we propose a global lightweight finger vein segmentation model, TRUnet, and build a lightweight Lightformer module and a plug-and-play module, Global-Lightweight block, in the proposed model respectively. The network not

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Harrowing

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