Image segmentation using multilevel thresholding: a research review
Image segmentation is a basic problem in computer vision and various image processing
applications. Over the years, commonly used image segmentation has become quite …
applications. Over the years, commonly used image segmentation has become quite …
Nature inspired optimization algorithms: a comprehensive overview
Nature performs complex tasks in a simple yet efficient way. Natural processes may seem
straightforward from outside but are composed of several inherently complicated sub …
straightforward from outside but are composed of several inherently complicated sub …
Chaotic random spare ant colony optimization for multi-threshold image segmentation of 2D Kapur entropy
D Zhao, L Liu, F Yu, AA Heidari, M Wang… - Knowledge-Based …, 2021 - Elsevier
Although the continuous version of ant colony optimizer (ACOR) has been successfully
applied to various problems, there is room to boost its stability and improve convergence …
applied to various problems, there is room to boost its stability and improve convergence …
[HTML][HTML] A comprehensive comparison among metaheuristics (MHs) for geohazard modeling using machine learning: Insights from a case study of landslide …
Abstract Machine learning (ML) has been extensively applied to model geohazards, yielding
tremendous success. However, researchers and practitioners still face challenges in …
tremendous success. However, researchers and practitioners still face challenges in …
Particle swarm optimization or differential evolution—A comparison
AP Piotrowski, JJ Napiorkowski… - Engineering Applications of …, 2023 - Elsevier
In the mid 1990s two landmark metaheuristics have been proposed: Particle Swarm
Optimization and Differential Evolution. Their initial versions were very simple, but rapidly …
Optimization and Differential Evolution. Their initial versions were very simple, but rapidly …
Cuckoo search algorithm and wind driven optimization based study of satellite image segmentation for multilevel thresholding using Kapur's entropy
The objective of image segmentation is to extract meaningful objects. A meaningful
segmentation selects the proper threshold values to optimize a criterion using entropy. The …
segmentation selects the proper threshold values to optimize a criterion using entropy. The …
Modified artificial bee colony based computationally efficient multilevel thresholding for satellite image segmentation using Kapur's, Otsu and Tsallis functions
In this paper, a modified artificial bee colony (MABC) algorithm based satellite image
segmentation using different objective function has been presented to find the optimal …
segmentation using different objective function has been presented to find the optimal …
Improved sine cosine algorithm with crossover scheme for global optimization
Abstract Sine Cosine Algorithm is a recently developed algorithm based on the
characteristics of sine and cosine trigonometric functions, to solve global optimization …
characteristics of sine and cosine trigonometric functions, to solve global optimization …
[图书][B] Computational intelligence applications in modeling and control
AT Azar, S Vaidyanathan - 2015 - Springer
The development of Computational Intelligence (CI) systems was inspired by observable
and imitable aspects of intelligent activity of human beings and nature. The essence of the …
and imitable aspects of intelligent activity of human beings and nature. The essence of the …
A competitive chain-based Harris Hawks Optimizer for global optimization and multi-level image thresholding problems
This paper presents an enhanced Harris Hawks Optimizer (HHO) to tackle global
optimization and determine the optimal threshold values for multi-level image segmentation …
optimization and determine the optimal threshold values for multi-level image segmentation …