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MeshFace photos have been widely used in many Chinese business organizations to protect ID face photos from being misused. The occlusions incurred by random meshes severely degenerate the performance of face verification systems, which raises the MeshFace verification problem between MeshFace and daily photos. Previous methods cast this problem as a typical low-level vision problem, i.e., blind inpainting...
Photorealistic frontal view synthesis from a single face image has a wide range of applications in the field of face recognition. Although data-driven deep learning methods have been proposed to address this problem by seeking solutions from ample face data, this problem is still challenging because it is intrinsically ill-posed. This paper proposes a Two-Pathway Generative Adversarial Network (TP-GAN)...
Intelligent video surveillance technology has been increasingly used in the field of transportation. Real-timely capturing traffic video data through the UAV is a new way to get road condition. In this paper, we set the statistics of road traffic flow as the starting point. After analyzing the characteristics of videos shot by the UAV, we choose to use the deep learning framework based on Faster-RCNN...
Computer vision algorithms are known to be extremely sensitive to the environmental conditions in which the data is captured, e.g., lighting conditions and target density. Tuning of parameters or choosing a completely new algorithm is often needed to achieve a certain performance level. In this paper, we focus on this problem and propose a framework to automatically choose the “best” algorithm-parameter...
Face verification between ID photos and life photos (FVBIL) is gaining traction with the rapid development of the Internet. However, ID photos provided by the Chinese administration center are often corrupted with wavy lines to prevent misuse, which poses great difficulty to accurate FVBIL. Therefore, this paper tries to improve the verification performance by studying a new problem, i.e. blind face...
A relatively underexplored question in fMRI is whether there are intrinsic differences in terms of signal composition patterns that can effectively characterize and differentiate task-based and resting state fMRI (tfMRI or rsfMRI) signals. In this paper, we propose a novel two-stage sparse representation framework to examine the fundamental difference between tfMRI and rsfMRI signals. In the first...
The computer networks experiment is practised in applied universities. Ii is necessary that the course of design thought should be established. Network software should be installed and experiment environment of network devices should be built perfectly. The teacher should design the comprehensive experiment contents and use bilingual teaching. The purpose is to cultivate network technology engineers...
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