Best regions for periocular recognition with NIR and visible images
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Publisher
IEEE
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http://xplorestaging.ieee.org/ielx7/6992914/7024995/07026010.pdf?arnumber=7026010
Cited by 12 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. MixQuantBio: Towards extreme face and periocular recognition model compression with mixed-precision quantization;Engineering Applications of Artificial Intelligence;2024-11
2. SyPer: Synthetic periocular data for quantized light-weight recognition in the NIR and visible domains;Image and Vision Computing;2023-07
3. Periocular biometrics and its relevance to partially masked faces: A survey;Computer Vision and Image Understanding;2023-01
4. Region specific and subimage based neighbour gradient feature extraction for robust periocular recognition;Journal of King Saud University - Computer and Information Sciences;2022-11
5. Lightweight Periocular Recognition through Low-bit Quantization;2022 IEEE International Joint Conference on Biometrics (IJCB);2022-10-10
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