Multimedia Tools and Applications - Deep learning has made essential contributions to the development of visual object detection and recognition. Identifying fast-moving objects from the viewpoint... 相似文献
Multimedia Tools and Applications - Almost all existing image encryption algorithms are only suitable for low-resolution images in the standard image library. When they are used to encrypt... 相似文献
Multimedia Tools and Applications - The pedestrian re-identification problem (i.e., re-id) is essential and pre-requisite in multi-camera video surveillance studies, provided the fact that... 相似文献
Palmprint recognition and palm vein recognition are two emerging biometrics technologies. In the past two decades, many traditional methods have been proposed for palmprint recognition and palm vein recognition, and have achieved impressive results. However, the research on deep learning-based palmprint recognition and palm vein recognition is still very preliminary. In this paper, in order to investigate the problem of deep learning based 2D and 3D palmprint recognition and palm vein recognition in-depth, we conduct performance evaluation of seventeen representative and classic convolutional neural networks (CNNs) on one 3D palmprint database, five 2D palmprint databases and two palm vein databases. A lot of experiments have been carried out in the conditions of different network structures, different learning rates, and different numbers of network layers. We have also conducted experiments on both separate data mode and mixed data mode. Experimental results show that these classic CNNs can achieve promising recognition results, and the recognition performance of recently proposed CNNs is better. Particularly, among classic CNNs, one of the recently proposed classic CNNs, i.e., EfficientNet achieves the best recognition accuracy. However, the recognition performance of classic CNNs is still slightly worse than that of some traditional recognition methods.
