most citedOpposition Based ElectromagnetismLike for Global Optimization

3 citations · 13 across the 18 of their papers we have counts for

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cs.CV20142 cited

An improved computer vision method for detecting white blood cells

Erik Cuevas, Margarita Diaz, Miguel Manzanares +2

The automatic detection of White Blood Cells (WBC) still remains as an unsolved issue in medical imaging. The analysis of WBC images has engaged researchers from fields of medicine…

cs.CV20142 cited

Multi Circle Detection on Images Using Artificial Bee Colony (ABC) Optimization

Erik Cuevas, Felipe Sencion-Echauri, Daniel Zaldivar +1

Hough transform (HT) has been the most common method for circle detection, exhibiting robustness, but adversely demanding considerable computational effort and large memory require…

cs.CV2014

A multilevel thresholding algorithm using Electromagnetism Optimization

Diego Oliva, Erik Cuevas, Gonzalo Pajares +2

Segmentation is one of the most important tasks in image processing. It consist in classify the pixels into two or more groups depending on their intensity levels and a threshold v…

cs.CV2014

Circle detection using electro-magnetism optimization

Erik Cuevas, Diego Oliva, Daniel Zaldivar +2

This paper describes a circle detection method based on Electromagnetism-Like Optimization (EMO). Circle detection has received considerable attention over the last years thanks to…

cs.CV2014

Circle detection using Discrete Differential Evolution Optimization

Erik Cuevas, Daniel Zaldivar, Marco Perez +1

This paper introduces a circle detection method based on Differential Evolution (DE) optimization. Just as circle detection has been lately considered as a fundamental component fo…

cs.CV2014

Seeking multi-thresholds for image segmentation with Learning Automata

Erik Cuevas, Daniel Zaldivar, Marco Perez

This paper explores the use of the Learning Automata (LA) algorithm to compute threshold selection for image segmentation as it is a critical preprocessing step for image analysis,…