Minarno, Agus Eko and Alfarizy, Muhammad Rifal and Hendryawan, Agus and Syaifuddin, Syaifuddin and Munarko, Yuda (2021) Pneumonia Classification using Gabor-Convolutional Neural Networks and Image Enhancement. In: 2021 9th International Conference on Information and Communication Technology (ICoICT). International Conference of Information and Communication Technology (ICoICT) (9). IEEE, Yogyakarta, Indonesia, pp. 180-185. ISBN Electronic ISBN:978-1-6654-0447-1 Print on Demand(PoD) ISBN:978-1-6654-4710-2
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Abstract
Pneumonia is acknowledged as a respiratory disease caused by bacterial and, viral or fungal infections and has a high mortality rate. Identification of pneumonia is typically performed with Chest X-Ray image, but hampered by other lung problems that have been experienced by the patient. Therefore, this study proposes a Convolutional Neural Networks method by adding a Gabor filter and an Image Enhancement Preprocessing technique. The application of the Gabor filter obtains the best accuracy with a value of 94.4% and a loss of 44%, while Image Enhancement obtains an accuracy of 87.8% and the best loss of 35.8%. Combining the Gabor filter and Image Enhancement obtains better accuracy and loss of 93.9% and 40% than utilizing these methods separately.
| Item Type: | Book Section / Proceedings |
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| Keywords: | Pneumonia, Gabor Filter, Convolutional Neural Network, Image Enhancement |
| Subjects: | T Technology > T Technology (General) |
| Divisions: | Faculty of Engineering > Department of Informatics (55201) |
| Depositing User: | maulana Maulana Chairudin |
| Date Deposited: | 16 Mar 2023 03:54 |
| Last Modified: | 16 Mar 2023 03:54 |
| URI : | http://eprints.umm.ac.id/id/eprint/99113 |
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