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A comprehensive survey of multi-level thresholding segmentation methods for image processing
In image processing, multi-level thresholding is a sophisticated technique used to delineate
regions of interest in images by identifying intensity levels that differentiate different …
regions of interest in images by identifying intensity levels that differentiate different …
DETDO: An adaptive hybrid dandelion optimizer for engineering optimization
Dandelion Optimizer (DO) is a recently proposed swarm intelligence algorithm that
coincides with the process of finding the best reproduction site for dandelion seeds …
coincides with the process of finding the best reproduction site for dandelion seeds …
Improved reptile search algorithm by salp swarm algorithm for medical image segmentation
This study proposes a novel nature-inspired meta-heuristic optimizer based on the Reptile
Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray …
Search Algorithm combed with Salp Swarm Algorithm for image segmentation using gray …
An enhanced chameleon swarm algorithm for global optimization and multi-level thresholding medical image segmentation
Medical image segmentation is crucial in using digital images for disease diagnosis,
particularly in post-processing tasks such as analysis and disease identification …
particularly in post-processing tasks such as analysis and disease identification …
DRNet: Dual-stage refinement network with boundary inference for RGB-D semantic segmentation of indoor scenes
Semantic segmentation is a dense pixel prediction task, and its accuracy depends on the
extraction of long-range contextual knowledge and refinement of segmentation boundaries …
extraction of long-range contextual knowledge and refinement of segmentation boundaries …
Chaotic opposition learning with mirror reflection and worst individual disturbance grey wolf optimizer for continuous global numerical optimization
The effective meta-heuristic technique known as the grey wolf optimizer (GWO) has shown
its proficiency. However, due to its reliance on the alpha wolf for guiding the position …
its proficiency. However, due to its reliance on the alpha wolf for guiding the position …
Multi-threshold image segmentation based on an improved whale optimization algorithm: A case study of Lupus Nephritis
J Shi, Y Chen, Z Cai, AA Heidari, H Chen… - … Signal Processing and …, 2024 - Elsevier
Lupus nephritis (LN) is a severe renal complication of systemic lupus erythematosus (SLE),
characterized by kidney inflammation and damage, often leading to significant morbidity and …
characterized by kidney inflammation and damage, often leading to significant morbidity and …
Multilevel thresholding with divergence measure and improved particle swarm optimization algorithm for crack image segmentation
F Nie, M Liu, P Zhang - Scientific Reports, 2024 - nature.com
Crack formation is a common phenomenon in engineering structures, which can cause
serious damage to the safety and health of these structures. An important method of …
serious damage to the safety and health of these structures. An important method of …
[HTML][HTML] Otsu multi-threshold image segmentation based on adaptive double-mutation differential evolution
A quick and effective way of segmenting images is the Otsu threshold method. However, the
complexity of time grows exponentially as the number of thresolds rises. The aim of this …
complexity of time grows exponentially as the number of thresolds rises. The aim of this …
Research Advances in Deep Learning for Image Semantic Segmentation Techniques
ZG **ao, TF Chai, NF Li, XF Shen, T Guan, J Tian… - Ieee …, 2024 - ieeexplore.ieee.org
Image semantic segmentation represents a significant area of research within the field of
computer vision. With the advent of deep learning, image semantic segmentation techniques …
computer vision. With the advent of deep learning, image semantic segmentation techniques …