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The diagnosis of diabetic retinopathy : An evaluation of different classifiers with the inception V3 model as a feature extractor

Diabetic Retinopathy (DR) is a type of eye disease that is caused by diabetes mellitus. The elevated blood glucose level causes the expansion of the blood vessels that results in the leaking of the blood and other fluids. DR is a silent disease in which those inflicted with it are unaware until irre...

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Main Authors: Farhan Nabil, Mohd Noor, Wan Hasbullah, Mohd Isa, Ismail, Mohd Khairuddin, Mohd Azraai, Mohd Razman, Musa, Rabiu Muazu, Ahmad Fakhri, Ab Nasir, Abdul Majeed, Anwar P. P.
Format: Conference or Workshop Item
Language:English
English
Published: Springer Science and Business Media Deutschland GmbH 2022
Subjects:
QA75 Electronic computers. Computer science
T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/39466/1/The%20Diagnosis%20of%20Diabetic%20Retinopathy_An%20Evaluation%20of%20Different%20Classifiers.pdf
http://umpir.ump.edu.my/id/eprint/39466/2/The%20diagnosis%20of%20diabetic%20retinopathy_An%20evaluation%20of%20different%20classi%EF%AC%81ers%20with%20the%20inception%20V3%20model%20as%20a%20feature%20extractor_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39466/
https://doi.org/10.1007/978-3-030-97672-9_35
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spelling my.ump.umpir.394662023-12-01T07:32:20Z http://umpir.ump.edu.my/id/eprint/39466/ The diagnosis of diabetic retinopathy : An evaluation of different classifiers with the inception V3 model as a feature extractor Farhan Nabil, Mohd Noor Wan Hasbullah, Mohd Isa Ismail, Mohd Khairuddin Mohd Azraai, Mohd Razman Musa, Rabiu Muazu Ahmad Fakhri, Ab Nasir Abdul Majeed, Anwar P. P. QA75 Electronic computers. Computer science T Technology (General) TA Engineering (General). Civil engineering (General) TJ Mechanical engineering and machinery TK Electrical engineering. Electronics Nuclear engineering Diabetic Retinopathy (DR) is a type of eye disease that is caused by diabetes mellitus. The elevated blood glucose level causes the expansion of the blood vessels that results in the leaking of the blood and other fluids. DR is a silent disease in which those inflicted with it are unaware until irregularities in the retina have advanced to the point where treatment is difficult or impossible to administer, resulting in them losing their sight completely. However, it is worth noting that early treatment can solve this problem. Hence, the purpose of this study is to develop a transfer learning pipeline for diagnosing DR. The data in the present study was obtained from the Kaggle database, and the pre-trained InceptionV3 model was employed to extract the features from the images acquired. The features are fed into the three different classifiers, namely, Support Vector Machine (SVM), k-Nearest Neighbour (kNN) and the Random Forest (RF). It was shown from the present investigation that the InceptionV3-SVM pipeline demonstrated the best performance by achieving 100%, 98% and 96% classification accuracy for the training, testing and validation dataset. The results further suggest the possible deployment of the pipeline for the diagnosis of DR. Springer Science and Business Media Deutschland GmbH 2022 Conference or Workshop Item PeerReviewed pdf en http://umpir.ump.edu.my/id/eprint/39466/1/The%20Diagnosis%20of%20Diabetic%20Retinopathy_An%20Evaluation%20of%20Different%20Classifiers.pdf pdf en http://umpir.ump.edu.my/id/eprint/39466/2/The%20diagnosis%20of%20diabetic%20retinopathy_An%20evaluation%20of%20different%20classi%EF%AC%81ers%20with%20the%20inception%20V3%20model%20as%20a%20feature%20extractor_ABS.pdf Farhan Nabil, Mohd Noor and Wan Hasbullah, Mohd Isa and Ismail, Mohd Khairuddin and Mohd Azraai, Mohd Razman and Musa, Rabiu Muazu and Ahmad Fakhri, Ab Nasir and Abdul Majeed, Anwar P. P. (2022) The diagnosis of diabetic retinopathy : An evaluation of different classifiers with the inception V3 model as a feature extractor. In: Lecture Notes in Networks and Systems; 9th International Conference on Robot Intelligence Technology and Applications, RiTA 2021, 16-17 December 2021 , Daejeon. pp. 392-397., 429 LNNS (276219). ISSN 2367-3370 ISBN 978-303097671-2 https://doi.org/10.1007/978-3-030-97672-9_35
institution Universiti Malaysia Pahang Al-Sultan Abdullah
building UMPSA Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
url_provider http://umpir.ump.edu.my/
language English
English
topic QA75 Electronic computers. Computer science
T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
spellingShingle QA75 Electronic computers. Computer science
T Technology (General)
TA Engineering (General). Civil engineering (General)
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
Farhan Nabil, Mohd Noor
Wan Hasbullah, Mohd Isa
Ismail, Mohd Khairuddin
Mohd Azraai, Mohd Razman
Musa, Rabiu Muazu
Ahmad Fakhri, Ab Nasir
Abdul Majeed, Anwar P. P.
The diagnosis of diabetic retinopathy : An evaluation of different classifiers with the inception V3 model as a feature extractor
description Diabetic Retinopathy (DR) is a type of eye disease that is caused by diabetes mellitus. The elevated blood glucose level causes the expansion of the blood vessels that results in the leaking of the blood and other fluids. DR is a silent disease in which those inflicted with it are unaware until irregularities in the retina have advanced to the point where treatment is difficult or impossible to administer, resulting in them losing their sight completely. However, it is worth noting that early treatment can solve this problem. Hence, the purpose of this study is to develop a transfer learning pipeline for diagnosing DR. The data in the present study was obtained from the Kaggle database, and the pre-trained InceptionV3 model was employed to extract the features from the images acquired. The features are fed into the three different classifiers, namely, Support Vector Machine (SVM), k-Nearest Neighbour (kNN) and the Random Forest (RF). It was shown from the present investigation that the InceptionV3-SVM pipeline demonstrated the best performance by achieving 100%, 98% and 96% classification accuracy for the training, testing and validation dataset. The results further suggest the possible deployment of the pipeline for the diagnosis of DR.
format Conference or Workshop Item
author Farhan Nabil, Mohd Noor
Wan Hasbullah, Mohd Isa
Ismail, Mohd Khairuddin
Mohd Azraai, Mohd Razman
Musa, Rabiu Muazu
Ahmad Fakhri, Ab Nasir
Abdul Majeed, Anwar P. P.
author_facet Farhan Nabil, Mohd Noor
Wan Hasbullah, Mohd Isa
Ismail, Mohd Khairuddin
Mohd Azraai, Mohd Razman
Musa, Rabiu Muazu
Ahmad Fakhri, Ab Nasir
Abdul Majeed, Anwar P. P.
author_sort Farhan Nabil, Mohd Noor
title The diagnosis of diabetic retinopathy : An evaluation of different classifiers with the inception V3 model as a feature extractor
title_short The diagnosis of diabetic retinopathy : An evaluation of different classifiers with the inception V3 model as a feature extractor
title_full The diagnosis of diabetic retinopathy : An evaluation of different classifiers with the inception V3 model as a feature extractor
title_fullStr The diagnosis of diabetic retinopathy : An evaluation of different classifiers with the inception V3 model as a feature extractor
title_full_unstemmed The diagnosis of diabetic retinopathy : An evaluation of different classifiers with the inception V3 model as a feature extractor
title_sort diagnosis of diabetic retinopathy : an evaluation of different classifiers with the inception v3 model as a feature extractor
publisher Springer Science and Business Media Deutschland GmbH
publishDate 2022
url http://umpir.ump.edu.my/id/eprint/39466/1/The%20Diagnosis%20of%20Diabetic%20Retinopathy_An%20Evaluation%20of%20Different%20Classifiers.pdf
http://umpir.ump.edu.my/id/eprint/39466/2/The%20diagnosis%20of%20diabetic%20retinopathy_An%20evaluation%20of%20different%20classi%EF%AC%81ers%20with%20the%20inception%20V3%20model%20as%20a%20feature%20extractor_ABS.pdf
http://umpir.ump.edu.my/id/eprint/39466/
https://doi.org/10.1007/978-3-030-97672-9_35
_version_ 1822923896493441024
score 13.232414

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