The paper introduces a new framework for feature learning in classification motivated by information theory. We first systematically study the information structure and present a n...
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
In this paper, we propose a novel image similarity learning approach based on Probabilistic Feature Matching (PFM). We consider the matching process as the bipartite graph matchin...
A novel approach to computer vision is outlined, involving the use of imprecise probabilities to connect a deep learning based hierarchical vision system with both local feature de...
In this paper, we present an efficient general-purpose objective no-reference (NR) image quality assessment (IQA) framework based on unsupervised feature learning. The goal is to...