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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書目名稱Biometric Recognition影響因子(影響力)




書目名稱Biometric Recognition影響因子(影響力)學(xué)科排名




書目名稱Biometric Recognition網(wǎng)絡(luò)公開度




書目名稱Biometric Recognition網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Biometric Recognition被引頻次




書目名稱Biometric Recognition被引頻次學(xué)科排名




書目名稱Biometric Recognition年度引用




書目名稱Biometric Recognition年度引用學(xué)科排名




書目名稱Biometric Recognition讀者反饋




書目名稱Biometric Recognition讀者反饋學(xué)科排名

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新鮮

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情節(jié)劇

Dionysia Kontogianni,Vassilios Oikonomidistions of patches are optimized globally. In the feature fusion stage, not only minutiae, but also ridge sampling points are fused to increase the information in the synthetic template. The proposed algorithm is tested on two datasets of FVC2002 and the experimental results show that it can achieve a great fingerprint mosaicking performance.

血統(tǒng)

Introduction: Language Diversity in Greece,ur pathways in the network. The method is verified on a popular databset, CASIA-B. The experimental results show that the proposed MSTN can observably improve the recognition rate and MSTN is a straightforward and effective solution. It also shows that there is great potential in gait feature extraction from the temporal domain.

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凝視

https://doi.org/10.1007/978-3-658-35650-7ngerprint. The experimental results show that the proposed algorithm can effectively eliminate the mosaicking gap and the positional deviation of misalignment and reprint, and improve the accuracy of fingerprint recognition.