antithetic
发表于 2025-3-21 17:55:26
书目名称Biometric Recognition影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0188177<br><br> <br><br>书目名称Biometric Recognition影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0188177<br><br> <br><br>书目名称Biometric Recognition网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0188177<br><br> <br><br>书目名称Biometric Recognition网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0188177<br><br> <br><br>书目名称Biometric Recognition被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0188177<br><br> <br><br>书目名称Biometric Recognition被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0188177<br><br> <br><br>书目名称Biometric Recognition年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0188177<br><br> <br><br>书目名称Biometric Recognition年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0188177<br><br> <br><br>书目名称Biometric Recognition读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0188177<br><br> <br><br>书目名称Biometric Recognition读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0188177<br><br> <br><br>
使高兴
发表于 2025-3-21 21:52:09
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hurricane
发表于 2025-3-22 03:06:50
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Cholagogue
发表于 2025-3-22 05:25:10
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incisive
发表于 2025-3-22 08:43:34
Soviet Language Planning since 1953,f fingerprint (FP), finger-vein (FV) and finger-knuckle (FKP), traditional feature-level fusion methods perform poorly. This paper proposed an end-to-end finger trimodal features fusion and recognition model based on CNN. For the purpose of constructing an end-to-end model, finger three-modal featur
贪心
发表于 2025-3-22 15:06:49
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蛙鸣声
发表于 2025-3-22 18:33:16
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deactivate
发表于 2025-3-22 23:23:36
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Abrupt
发表于 2025-3-23 04:01:10
https://doi.org/10.1057/9781137316202f portrait Thangka image retrieval from the perspective of re-identifying the figures in the images. Based on state-of-the-art re-identification methods, we further improve them by exploiting several tricks. We also investigate the impact of different cropping methods to evaluate the contribution of
真
发表于 2025-3-23 07:27:34
Research and Practice in Applied Linguisticss but also loss of discriminative features. To address the issue, this paper proposes a novel adversarial disentangled features learning (ADFL) method for recognizing expressions on occluded face images. Unlike previous methods, our method defines an explicit noise component in addition to the ident