An improved dolphin swarm algorithm based on Kernel Fuzzy C-means in the application of solving the optimal problems of large-scale function

W Qiao, Z Yang - Ieee Access, 2019 - ieeexplore.ieee.org
The solution of high dimensional function has always been a hot topic. In this paper, a novel
algorithm based on Kernel Fuzzy C-means and dolphin swarm algorithm are proposed to …

Classification and Diagnosis of Alzheimer's Disease based on a combination of Deep Features and Machine Learning

M Saim, F Amel - 2022 7th International Conference on Image …, 2022 - ieeexplore.ieee.org
Alzheimer's disease (AD) is a neurodegenerative illness that causes structural changes in
the brain over time. Furthermore, various symptoms, most notably memory disorder, relate to …

[PDF][PDF] Hybrid segmentation approach for different medical image modalities

W El-Shafai, AA Mahmoud… - CMC-COMPUTERS …, 2022 - cdn.techscience.cn
The segmentation process requires separating the image region into sub-regions of similar
properties. Each sub-region has a group of pixels having the same characteristics, such as …

Micro‐segmentation of retinal image lesions in diabetic retinopathy using energy‐based fuzzy C‐Means clustering (EFM‐FCM)

H Naz, R Nijhawan, NJ Ahuja, T Saba… - Microscopy …, 2024 - Wiley Online Library
Diabetic retinopathy (DR) is a prevalent cause of global visual impairment, contributing to
approximately 4.8% of blindness cases worldwide as reported by the World Health …

Review of various Artificial Intelligence Techniques and its applications

S Varshney, R Jigyasu, A Sharma… - IOP Conference Series …, 2019 - iopscience.iop.org
With the upgrading needs of automation and prediction requirements in the industries,
automation for improving the quality of the product and prediction of the product cycle to …

MRI retinal image segmentation using integrated approach of fuzzy c-means clustering, and active contouring

R Chauhan, N Kaur, C Tiwari - 2021 11th International …, 2021 - ieeexplore.ieee.org
In order to locate the different objects, shapes and structures in digital images, segmentation
is the most acceptable and popular choice. This paper combines fuzzy c-means clustering …

Agrupamiento difuso titubeante para tareas de segmentación de imágenes y reconocimiento de patrones

VV Vela Rincon - 2022 - 51.143.95.221
Entre las distintas áreas de la Inteligencia Artificial se encuentra el Reconocimiento de
Patrones y la Visión por Computadora, que se han beneficiado utilizando los métodos de …

[PDF][PDF] Enhanced Image Segmentation: Merging Fuzzy K-Means and Fuzzy C-Means Clustering Algorithms for Medical Applications

KM Aljebory, TS Mohammed… - Computer Science and …, 2021 - researchgate.net
Separating an image into regions according to some criterion is called image segmentation.
This paper presents an algorithm that combines the fuzzy k-means (FKM) and fuzzy c-means …

Effect of Data Parameters and Seeding on k-Means and k-Medoids

P Olukanmi, F Nelwamondo… - … Conference on Artificial …, 2020 - ieeexplore.ieee.org
k-means and k-medoids are arguably the two most popular clustering methods. This paper
reports an empirical study of the relative (de) merits of these two methods. We compare their …

A Novel Computer Aided Diagnosis System for Lung Tumor Based on Support Vector Machine

R Mothkur, KM Poornima - … Conference on Image Processing and Capsule …, 2022 - Springer
A quick internet search reveals that lung cancer kills more people each year than colon,
breast, and prostate cancers. These frightening facts prompted us to deeply look into the …