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.
Machine Intelligence Research - One of the most significant challenges in the neuroscience community is to understand how the human brain works. Recent progress in neuroimaging techniques have... 相似文献
The viscous damping coefficient(VDC) of hydraulic actuators is crucial for system modeling,control and dynamic characteristic analysis.Currently,the researches on hydraulic actuators focus on behavior assessment,promotion of control performance and efficiency.However,the estimation of the VDC is difficult due to a lack of study.Firstly,using two types of hydraulic cylinders,behaviors of the VDC are experimentally examined with velocities and pressure variations.For the tested plunger type hydraulic cylinder,the exponential model B=αυ~(-β),(α0,β0)or B=α_1e~(-β_1υ)+α_2e~(-β_2υ)(α_1,α_20,β_1,β_20),fits the relation between the VDC and velocities for a given pressure of chamber with high precision.The magnitude of the VDC decreases almost linearly under certain velocities when increasing the chamber pressure from 0.6 MPa to 6.0 MPa.Furthermore,the effects of the chamber pressures on the VDC of piston and plunge type hydraulic cylinders are different due to different sealing types.In order to investigate the VDC of a plunger type hydraulic actuator drastically,a steady-state numerical model has been developed to describe the mechanism incorporating tandem seal lubrication,back-up ring related friction behaviors and shear stress of fluid.It is shown that the simulated results of VDC agree with the measured results with a good accuracy.The proposed method provides an instruction to predict the VDC in system modeling and analysis. 相似文献