Convolutional Neural Network Modeling for Eye Disease Recognition
DOI:
https://doi.org/10.3991/ijoe.v18i09.29847Keywords:
Eye diseases, Osteopathic Expert System, CNN, VGG16, Performance Metrics, AccuracyAbstract
The eye is an important sensing organ of the human body, as it reacts to light and allows vision of humans. Many Bangladeshi people become nearsighted when it comes to the awareness of vision loss due to eye disease. Many Bangladeshis people are more concerned about losing their money than getting nearsighted or blind, due to a combination of poverty and illiteracy. With this view, this paper proposes an osteopathic expert system that can deal with an image of the eye and recognize the disease. Here, we have focused on the three most common eye diseases in Bangladesh, namely cataract, chalazion, and squint. We have modeled six convolutional neural networks (CNN’s), namely VGG16, VGG19, MobileNet, Xception, InceptionV3, and DenseNet121 to recognize the diseases. We have reached the best configuration of each of these CNN models after adequate investigation. After performing satisfactory experimentation, we have found that the MobileNet model gives the best performance based on accuracy, precision, recall, and F1-score. At last, we have compared our findings with the recently reported relevant works to show their efficacy.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2022 Md. Ashikul Aziz Siddique, Jannatul Ferdouse, Md. Tarek Habib, Md. Jueal Mia, Prof. Mohammad Shorif Uddin
This work is licensed under a Creative Commons Attribution 4.0 International License.
The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.
