This paper summarizes the top state-of-the-art contributions reported on the MNIST dataset
for handwritten digit recognition. This dataset has been extensively used to validate novel …

The visual exploration of retinal blood vessels assists ophthalmologists in the diagnoses of
different abnormalities of the eyes such as diabetic retinopathy, glaucoma, cardiovascular …

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 …

In this paper, we propose a deep neural network architecture for object recognition based on
recurrent neural networks. The proposed network, called ReNet, replaces the ubiquitous …

Developing efficient vessel-tracking algorithms is crucial for imaging-based diagnosis and
treatment of vascular diseases. Vessel tracking aims to solve recognition problems such as …

Interest point detection is one of the most fundamental and critical problems in computer
vision and image processing. In this paper, we carry out a comprehensive review on image …

Segmentation of retinal fundus images is a crucial part of medical diagnosis. Automatic
extraction of blood vessels in low-quality retinal images remains a challenging problem. In …

The inspection of retinal fundus images allows medical doctors to diagnose various
pathologies. Computer-aided diagnosis systems can be used to assist in this process. As a …

Scale-invariance, good localization and robustness to noise and distortions are the main
properties that a local feature detector should possess. Most existing local feature detectors …

Simple cells in primary visual cortex are believed to extract local contour information from a
visual scene. The 2D Gabor function (GF) model has gained particular popularity as a …