Due to object detection's close relationship with video analysis and image understanding, it
has attracted much research attention in recent years. Traditional object detection methods …

In this paper, we first describe the basics of the field of cancer diagnosis, which includes
steps of cancer diagnosis followed by the typical classification methods used by doctors …

Recent progress on saliency detection is substantial, benefiting mostly from the explosive
development of Convolutional Neural Networks (CNNs). Semantic segmentation and …

Detecting and segmenting salient objects from natural scenes, often referred to as salient
object detection, has attracted great interest in computer vision. While many models have …

A key problem in salient object detection is how to effectively model the semantic properties
of salient objects in a data-driven manner. In this paper, we propose a multi-task deep …

Although depth information plays an important role in the human vision system, it is not yet
well-explored in existing visual saliency computational models. In this work, we first …

Salient object detection has been attracting a lot of interest, and recently various heuristic
computational models have been designed. In this paper, we regard saliency map …

We extensively compare, qualitatively and quantitatively, 41 state-of-the-art models (29
salient object detection, 10 fixation prediction, 1 objectness, and 1 baseline) over seven …

Objective: Segmentation of skin lesions is an important step in the automated computer
aided diagnosis of melanoma. However, existing segmentation methods have a tendency to …

Most existing zero-shot learning approaches exploit transfer learning via an intermediate
semantic representation shared between an annotated auxiliary dataset and a target dataset …