The search for powerful optimizers has led to the development of a multitude of
metaheuristic algorithms inspired from all areas. This work focuses on the animal kingdom …

Background and objective: Automatic segmentation of retinal blood vessels makes a major
contribution in CADx of various ophthalmic and cardiovascular diseases. A procedure to …

Segmentation is an essential preprocessing step in techniques for image analysis. The
automatic segmentation of brain magnetic resonance imaging has been exhaustively …

Image segmentation is an indispensable part of computer vision applications, and image
thresholding is a popular one due to its simplicity and robustness. Generalised Masi entropy …

One of today's inspiring issues is the 2D histogram-based multilevel threshold selection
which is used for segmenting images into several regions. The image analysis warrants …

Medical image segmentation often suffers from the challenges of class imbalance, blurred
target boundaries, and small data. How to establish a framework to automatically segment …

Chest radiography is one of the most widely used imaging techniques for the detection and
diagnosis of lung diseases. However, the correct extraction of information in these images is …

Accurate measurement and identification of the number and length of yarn hairiness is
crucial for spinning process optimization and product quality control. However, the existing …

Finding the optimum subset of genes for microarray classification is laborious because
microarray data are often high-dimensional and contain many irrelevant and redundant …

Semantic segmentation of road scene is the key technology of autonomous driving, and the
improvement of convolutional neural network architecture promotes the improvement of …