17 citations · 40 across the 18 of their papers we have counts for
8 papers · 1 filter
Improving Spiking Sparse Recovery via Non-Convex Penalties
Xiang Zhang, Lei Yu, Gang Zheng
Compared with digital methods, sparse recovery based on spiking neural networks has great advantages like high computational efficiency and low power-consumption. However, current…
Mixed Noise Removal with Pareto Prior
Zhou Liu, Lei Yu, Gui-Song Xia +1
Denoising images contaminated by the mixture of additive white Gaussian noise (AWGN) and impulse noise (IN) is an essential but challenging problem. The presence of impulsive distu…
Structure-Aware Network for Lane Marker Extraction with Dynamic Vision Sensor
Wensheng Cheng, Hao Luo, Wen Yang +2
Lane marker extraction is a basic yet necessary task for autonomous driving. Although past years have witnessed major advances in lane marker extraction with deep learning models,…
Event Enhanced High-Quality Image Recovery
Bishan Wang, Jingwei He, Lei Yu +2
With extremely high temporal resolution, event cameras have a large potential for robotics and computer vision. However, their asynchronous imaging mechanism often aggravates the m…
Implicit Euler ODE Networks for Single-Image Dehazing
Jiawei Shen, Zhuoyan Li, Lei Yu +2
Deep convolutional neural networks (CNN) have been applied for image dehazing tasks, where the residual network (ResNet) is often adopted as the basic component to avoid the vanish…
Kernel Learning for High-Resolution Time-Frequency Distribution
Lei Jiang, Haijian Zhang, Lei Yu +1
The design of high-resolution and cross-term (CT) free time-frequency distributions (TFDs) has been an open problem. Classical kernel based methods are limited by the trade-off bet…
Single Image Deraining with Continuous Rain Density Estimation
Jingwei He, Lei Yu, Gui-Song Xia +1
Single image deraining (SIDR) often suffers from over/under deraining due to the nonuniformity of rain densities and the variety of raindrop scales. In this paper, we propose a \te…
Robust Time-Frequency Reconstruction by Learning Structured Sparsity
Lei Jiang, Haijian Zhang, Lei Yu
Time-frequency distributions (TFDs) play a vital role in providing descriptive analysis of non-stationary signals involved in realistic scenarios. It is well known that low time-fr…