Fundus Görüntülerinden Derin Öğrenme Teknikleri ile Glokom Hastalığının Tespiti
Öz
Anahtar Kelimeler
Kaynakça
- Ahmad, S., Ansari, S. U., Haider, U., Javed, K., Rahman, J. U., & Anwar, S. (2022). Confusion matrix-based modularity induction into pretrained CNN. Multimedia Tools and Applications, 1-27.
- Alghamdi, H. S., Tang, H. L., Waheeb, S. A., & Peto, T. (2016, October). Automatic optic disc abnormality detection in fundus images: A deep learning approach. In Ophthalmic Medical Image Analysis International Workshop (Vol. 3, No. 2016). University of Iowa.
- Almazroa, A., Alodhayb, S., Burman, R., Sun, W., Raahemifar, K., & Lakshminarayanan, V. (2015, October). Optic cup segmentation based on extracting blood vessel kinks and cup thresholding using Type-II fuzzy approach. In 2015 2nd International Conference on Opto-Electronics and Applied Optics (IEM OPTRONIX) (pp. 1-3). IEEE.
- Alsulami, F., Alseleahbi, H., Alsaedi, R., Almaghdawi, R., Alafif, T., Ikram, M., ... & WeTeach, W. HiGANCNN: A Hybrid Generative Adversarial Network and Convolutional Neural Network for Glaucoma Detection.
- Carrillo, J., Bautista, L., Villamizar, J., Rueda, J., & Sanchez, M. (2019, April). Glaucoma detection using fundus images of the eye. In 2019 XXII Symposium on Image, Signal Processing and Artificial Vision (STSIVA) (pp. 1-4). IEEE.
- Chen, X., Xu, Y., Wong, D. W. K., Wong, T. Y., & Liu, J. (2015, August). Glaucoma detection based on deep convolutional neural network. In 2015 37th annual international conference of the IEEE engineering in medicine and biology society (EMBC) (pp. 715-718). IEEE.
- Cho, H., Hwang, Y. H., Chung, J. K., Lee, K. B., Park, J. S., Kim, H. G., & Jeong, J. H. (2021). Deep learning ensemble method for classifying glaucoma stages using fundus photographs and convolutional neural networks. Current eye research, 46(10), 1516-1524.
- Clifton, L., Clifton, D. A., Pimentel, M. A., Watkinson, P. J., & Tarassenko, L. (2012). Gaussian processes for personalized e-health monitoring with wearable sensors. IEEE Transactions on Biomedical Engineering, 60(1), 193-197.
Ayrıntılar
Birincil Dil
Türkçe
Konular
Mühendislik
Bölüm
Araştırma Makalesi
Yazarlar
Özcan Yıldırım
0000-0003-2776-5081
Türkiye
Yayımlanma Tarihi
31 Aralık 2022
Gönderilme Tarihi
8 Aralık 2022
Kabul Tarihi
17 Aralık 2022
Yayımlandığı Sayı
Yıl 2022 Sayı: 44
Cited By
ViT Tabanlı Hibrit Öğrenme Yöntemleri ile Göz Tansiyonu Hastalığının Tespiti
Düzce Üniversitesi Bilim ve Teknoloji Dergisi
https://doi.org/10.29130/dubited.1494138