5 papers
Deep Learning with Inaccurate Training Data for Image Restoration
Bolin Liu, Xiao Shu, Xiaolin Wu
In many applications of deep learning, particularly those in image restoration, it is either very difficult, prohibitively expensive, or outright impossible to obtain paired traini…
Demoiréing of Camera-Captured Screen Images Using Deep Convolutional Neural Network
Bolin Liu, Xiao Shu, Xiaolin Wu
Taking photos of optoelectronic displays is a direct and spontaneous way of transferring data and keeping records, which is widely practiced. However, due to the analog signal inte…
Learning-Based Dequantization For Image Restoration Against Extremely Poor Illumination
Chang Liu, Xiaolin Wu, Xiao Shu
All existing image enhancement methods, such as HDR tone mapping, cannot recover A/D quantization losses due to insufficient or excessive lighting, (underflow and overflow problems…
Cognitive Deficit of Deep Learning in Numerosity
Xiaolin Wu, Xi Zhang, Xiao Shu
Subitizing, or the sense of small natural numbers, is an innate cognitive function of humans and primates; it responds to visual stimuli prior to the development of any symbolic sk…
Fast Screening Algorithm for Rotation and Scale Invariant Template Matching
Bolin Liu, Xiao Shu, Xiaolin Wu
This paper presents a generic pre-processor for expediting conventional template matching techniques. Instead of locating the best matched patch in the reference image to a query t…