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Titlebook: Biometric Recognition; 13th Chinese Confere Jie Zhou,Yunhong Wang,Zhenhua Guo Conference proceedings 2018 Springer Nature Switzerland AG 20

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Palmprint Recognition Using Siamese Networkrecognition outcome with an Equal Error Rate (EER) of 0.2819%. To test the robustness of the proposed algorithm, we collected a palmprint dataset called XJTU from the practical daily environment. On XJTU, the EER of our method is 4.559%, which highlighted a promising potential of the usage of palmprint in personal identification system.
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Optimal Parameter Selection for 3D Palmprint Acquisition Systemoped a new scheme to tune the initial system parameters to balance the tradeoff of device cost, volume, and data generation time. The samples collected by our proposed device have proved its effectiveness and advantages. The system is easy to implement and will promote the application of 3D palmprint.
发表于 2025-3-30 18:18:15 | 显示全部楼层
Residual Gating Fusion Network for Human Action Recognitionalysis tasks. We evaluate our RGFN on two standard benchmarks, i.e., UCF101 and HMDB51, and analyze the designs of convolution network. Experiments results demonstrate the advantages of RGFN, achieving the state-of-the-art performance.
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Cross-Cascading Regression for Simultaneous Head Pose Estimation and Facial Landmark Detectionwe adopt integral operation for both pose and landmark coordinate regression, and exploit expectation instead of maximum value to estimate head pose and locate facial landmarks. Results of extensive experiments demonstrate that our approach achieves state-of-the-art performance on the challenging AFLW dataset.
发表于 2025-3-31 07:03:09 | 显示全部楼层
Real Time Violence Detection Based on Deep Spatio-Temporal Featuresppearance and motion information. We compared the proposed model with several state-of-the-art methods on two datasets. The results are promising and the proposed method can achieve real-time performance of 30 fps.
发表于 2025-3-31 09:36:51 | 显示全部楼层
0302-9743 2018. . The 79 regular papers presented in this book were carefully reviewed and selected from 112 submissions. Thepapers cover a wide range of topics such as Biometrics, Speech recognition, Activity recognition and understanding, Online handwriting recognition, System forensics, Multi-factor authe
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A New Hand Shape Recognition Algorithm Based on Delaunay Triangulationatures. Thus, we propose to form a more robust and non-parametric finger central axis extraction algorithm, by using a Delaunay triangulation algorithm. We show that our robust algorithm achieves the recognition rate of 99.89% on our database, while the mean time of feature extraction is 0.09 s.
发表于 2025-3-31 23:19:42 | 显示全部楼层
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