Image Processing and Machine Learning Techniques for Diabetic Retinopathy Detection: A Review

2020 ◽  
pp. 136-154
Author(s):  
Sarni Suhaila Rahim ◽  
Vasile Palade ◽  
Andreas Holzinger
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Diabetic Retinopathy ◽  
Machine Learning Techniques ◽  
Learning Techniques

scholarly journals Integration of image segmentation and fuzzy theory to improve the accuracy of damage detection areas in traffic accidents

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Majid Amirfakhrian ◽  
Mahboub Parhizkar
Keyword(s):  
Machine Learning ◽  
Image Processing ◽  
Machine Vision ◽  
Traffic Accidents ◽  
Fuzzy Theory ◽  
Machine Learning Techniques ◽  
Industrial Setting ◽  
Technological Advances ◽  
Learning Techniques ◽  
Wide Range

AbstractIn the next decade, machine vision technology will have an enormous impact on industrial works because of the latest technological advances in this field. These advances are so significant that the use of this technology is now essential. Machine vision is the process of using a wide range of technologies and methods in providing automated inspections in an industrial setting based on imaging, process control, and robot guidance. One of the applications of machine vision is to diagnose traffic accidents. Moreover, car vision is utilized for detecting the amount of damage to vehicles during traffic accidents. In this article, using image processing and machine learning techniques, a new method is presented to improve the accuracy of detecting damaged areas in traffic accidents. Evaluating the proposed method and comparing it with previous works showed that the proposed method is more accurate in identifying damaged areas and it has a shorter execution time.

scholarly journals A Survey on Diagnosis and Analysis of Diabetic Retinopathy using Feature Selection

2020 ◽  
pp. 170-176
Author(s):  
Amalu Michael ◽  
Deepa S S
Keyword(s):  
Machine Learning ◽  
Feature Selection ◽  
Diabetic Retinopathy ◽  
High Ratio ◽  
Training Data ◽  
Machine Learning Techniques ◽  
Learning Techniques ◽  
Diabetic Eye Disease ◽  
Selection Mechanisms ◽  
Feature Selection Techniques

Diabetic retinopathy is one of the common forms of diabetic eye disease. DR occurs due to a high ratio of glucose in the blood, which causes alterations in the retinal vessels. Machine learning may be a broad multidisciplinary field that has its roots in statistics, algebra, data processing, and information analytics, etc. Machine learning is used to discover patterns from medical data and provide an efficient way to predict diseases.ML is an application of artificial intelligence it collects information from training data. There are several machine learning techniques are used for the diagnosis of diabetic retinopathy. This paper mainly focuses on the survey of such techniques and also various feature selection mechanisms. This study provides the basic categorization of feature selection techniques and discussing their use.

Sign in / Sign up

Export Citation Format

Share Document