@inproceedings{62aef0460c9348b4ab6ece688bb6c38d,
title = "Image classification method in DR image based on transfer learning",
abstract = "Until now many cancer cases have been discovered in their early stages based on Computer Aided Diagnosis (CAD) system. There are many methods in the medical image processing field have been proposed to address this issue, and the result of these methods was deficient. Further, the application of AI in DR images is not widespread in hospitals. The classification process in the DR image is more difficult than other types of images. In this paper, we use transfer learning which is based on Inception V3 model to classify the DR images. We used the weight of Inception V3 model which was trained in the ImageNet dataset, and fine-tuning in our own dataset. Comparing to other proposed methods, our result had a higher accuracy.",
keywords = "CAD, DR images, medical image, Transfer Learning",
author = "Alsabahi, {Y. A.L.} and Lei Fan and Xiaoyi Feng",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 8th International Conference on Image Processing Theory, Tools and Applications, IPTA 2018 ; Conference date: 07-11-2018 Through 10-11-2018",
year = "2019",
month = jan,
day = "10",
doi = "10.1109/IPTA.2018.8608157",
language = "英语",
series = "2018 8th International Conference on Image Processing Theory, Tools and Applications, IPTA 2018 - Proceedings",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 8th International Conference on Image Processing Theory, Tools and Applications, IPTA 2018 - Proceedings",
}
