The allocation of attention to objects raises several intriguing questions: What are objects,
how does attention access them, what anatomical regions are involved? Here, we review …

Log-polar imaging consists of a type of methods that represent visual information with a
space-variant resolution inspired by the visual system of mammals. It has been studied for …

Recently, neural networks have been widely used in e-commerce recommender systems,
owing to the rapid development of deep learning. We formalize the recommender system as …

Modeling visual attention-particularly stimulus-driven, saliency-based attention-has been a
very active research area over the past 25 years. Many different models of attention are now …

Visual saliency modeling for images and videos is treated as two independent tasks in
recent computer vision literature. While image saliency modeling is a well-studied problem …

This paper considers the problem of multi-label thorax disease classification on chest X-ray
images. Identifying one or more pathologies from a chest X-ray image is often hindered by …

Salient areas in natural scenes are generally regarded as areas which the human eye will
typically focus on, and finding these areas is the key step in object detection. In computer …

Selective visual attention is believed to be responsible for serializing visual information for
recognizing one object at a time in a complex scene. But how can we attend to objects …

It is a very challenging problem to well simulate visual attention mechanisms for content-
based image retrieval. In this paper, we propose a novel computational visual attention …

Based on concepts of the human visual system, computational visual attention systems aim
to detect regions of interest in images. Psychologists, neurobiologists, and computer …