DEEP‐LSTM BASED RED FOX OPTIMIZATION ALGORITHM FOR DIABETIC RETINOPATHY DETECTION AND CLASSIFICATION

2021 ◽  
Author(s):  
R. Pugal Priya ◽  
T. S. Sivarani ◽  
A. Gnana Saravanan
Keyword(s):  
Diabetic Retinopathy ◽  
Optimization Algorithm ◽  
Red Fox

Red fox optimization algorithm

2021 ◽  
Vol 166 ◽  
pp. 114107
Author(s):  
Dawid Połap ◽  
Marcin Woźniak
Keyword(s):  
Optimization Algorithm ◽  
Red Fox

scholarly journals Optimal Diagnosis of COVID-19 Based on Convolutional Neural Network and Red Fox Optimization Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ehsan Khorami ◽  
Fatemeh Mahdi Babaei ◽  
Aidin Azadeh
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Optimization Algorithm ◽  
Red Fox ◽  
Region Of Interest ◽  
Disease Spread ◽  
Discrete Wavelet ◽  
Diagnostic Systems ◽  
Human Errors ◽  
X Ray

SARS-CoV-2 is a specific type of Coronavirus that was firstly reported in China in December 2019 and is the causative agent of coronavirus disease 2019 (COVID-19). In March 2020, this disease spread to different parts of the world causing a global pandemic. Although this disease is still increasing exponentially day by day, early diagnosis of this disease is very important to reduce the death rate and to reduce the prevalence of this pandemic. Since there are sometimes human errors by physicians in the diagnosis of this disease, using computer-aided diagnostic systems can be helpful to get more accurate results. In this paper, chest X-ray images have been examined using a new pipeline machine vision-based system to provide more accurate results. In the proposed method, after preprocessing the input X-ray images, the region of interest has been segmented. Then, a combined gray-level cooccurrence matrix (GLCM) and Discrete Wavelet Transform (DWT) features have been extracted from the processed images. Finally, an improved version of Convolutional Neural Network (CNN) based on the Red Fox Optimization algorithm is employed for the classification of the images based on the features. The proposed method is validated by performing to three datasets and its results are compared with some state-of-the-art methods. The final results show that the suggested method has proper efficiency toward the others for the diagnosis of COVID-19.

Skin cancer detection using Kernel Fuzzy C-means and Developed Red Fox Optimization algorithm

2022 ◽  
Vol 71 ◽  
pp. 103160
Author(s):  
Zexian Fu ◽  
Jing An ◽  
Qiuyu Yang ◽  
Haojun Yuan ◽  
Yuhang Sun ◽  
...  
Keyword(s):  
Skin Cancer ◽  
Cancer Detection ◽  
Optimization Algorithm ◽  
Red Fox ◽  
Fuzzy C Means ◽  
Skin Cancer Detection
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