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

小爭(zhēng)吵

拋棄的貨物

syring

Affective Prior Topology Graph Guided Facial Expression Recognitionly concentrated on emotion classification or sentiment levels, disregarding the crucial dependencies between these factors that are vital for perceiving human emotions. To address this problem, we propose a novel affective priori topology graph network (AptGATs). AptGATs explicitly captures the topo

VEIL

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/b/image/188172.jpg

lattice

Gilles Barthe,Benjamin Grégoire,Colin Ribaistration 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

staging

Overdose

More on Generalized Derivatives,mprint 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,

分發(fā)

Orgasm

https://doi.org/10.1057/978-1-137-58746-6ly, many existing methods have shown relatively satisfying performance, but there are still several problems such as the limited patterns extracted by single feature extraction approach and the huge gap between hand-crafted feature-based approaches and deep learning feature-based approaches. To this

DEFER

Open-ended Procedural Semanticscies in finger vein (FV) recognition, there still remain some unresolved issues, including high model complexity and memory cost, as well as insufficient training samples. To address these issues, we propose an unsupervised spiking neural network for finger vein recognition (hereinafter dubbed ‘FV-S