3 citations · 4 across the 2 of their papers we have counts for
3 papers
cs.CV2022★ 1 cited
ExpNet: A unified network for Expert-Level Classification
Junde Wu, Huihui Fang, Yehui Yang +4
Different from the general visual classification, some classification tasks are more challenging as they need the professional categories of the images. In the paper, we call them…
eess.IV2020★ 3 cited
Learning an Adaptive Model for Extreme Low-light Raw Image Processing
Qingxu Fu, Xiaoguang Di, Yu Zhang
Low-light images suffer from severe noise and low illumination. Current deep learning models that are trained with real-world images have excellent noise reduction, but a ratio par…
cs.CV2019
Integrating neural networks into the blind deblurring framework to compete with the end-to-end learning-based methods
Junde Wu, Xiaoguang Di, Jiehao Huang +1
Recently, end-to-end learning-based methods based on deep neural network (DNN) have been proven effective for blind deblurring. Without human-made assumptions and numerical algorit…