Titlebook: Biometric Recognition; 17th Chinese Confere Wei Jia,Wenxiong Kang,Jun Wang Conference proceedings 2023 The Editor(s) (if applicable) and Th

抛射物

Left-Atrium

accessory

Fluid Construction Grammar on Real Robotsralization model MultiBioGM. Experimental results on three multimodal datasets demonstrate the effectiveness of our model for biometrics, which achieves 0.098%, 0.024%, and 0.117% EERs on unobserved data.

使人入神

Lecture Notes in Computer Sciencerating these multi-dimensional feature nets, our proposed integrated network can extract the robust and complementary age features between RGB and depth modalities. Extensive experimental results on the widely used databases clearly demonstrate the effectiveness of our proposed method.

glacial

天气

Patrick Stevenson,Clare Mar-Molineroed on AptG that models the relationships within the affective labels. Moreover, we propose a parallel superposition mechanism to obtain a richer information representation. Experiments on the wild datasets AffectNet and Aff-Wild2 validate the effectiveness of our method. The results of public benchm

丛林

Unsupervised Fingerprint Dense Registrationistration methods need sufficient amount of labeled fingerprint pairs which are difficult to obtain. In addition, the training data itself may not include enough variety of fingerprints thus limit such methods’ performance. In this work, we propose an unsupervised end-to-end framework for fingerprin

石墨

敬礼

U-PISRNet: A Unet-Shape Palmprint Image Super-Resolution Networkmprint recognition methods focus only feature representation and matching under an assumption that palmprint images are high-quality, while practical palmprint images are usually captured by various cameras under diverse backgrounds, heavily reducing the quality of palmprint images. To address this,

Optometrist