In computer vision, edge and object contour detection is essential for higher-level vision
tasks, such as shape matching, visual salience, image segmentation, and object recognition …

Object contour plays an important role in fields such as semantic segmentation and image
classification. However, the extraction of contour is a difficult task, especially when the …

Retinal imaging provides a non-invasive opportunity for the diagnosis of several medical
pathologies. The automatic segmentation of the vessel tree is an important pre-processing …

Background: Keypoint detection is important for many computer vision applications. Existing
methods suffer from insufficient selectivity regarding the shape properties of features and are …

Studies in biological vision have always been a great source of inspiration for design of
computer vision algorithms. In the past, several successful methods were designed with …

Livestock management involves the monitoring of farm animals by tracking certain
physiological and phenotypical characteristics over time. In the dairy industry, for instance …

Background: The vascular tree observed in a retinal fundus image can provide clues for
cardiovascular diseases. Its analysis requires the identification of vessel bifurcations and …

Convolutional neural networks (CNNs) lack robustness to test image corruptions that are not
seen during training. In this paper, we propose a new layer for CNNs that increases their …

Feature integration theory can be regarded as a perception theory, but the extraction of
visual features using such a theory within the CBIR framework is a challenging problem. To …

The popularity and the appeal of systems which are able to automatically determine the
gender from face images are growing rapidly. Such a great interest arises from the wide …