Towards Federated-Deep Learning-Based Glaucoma Detection from Color Fundus Images
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-97-1923-5_19
Reference27 articles.
1. Schuster AK, Erb C, Hoffmann EM, Dietlein T, Pfeiffer N (2020) The diagnosis and treatment of glaucoma. Deutsches Ärzteblatt Int 117(13):225
2. Chen X (2015) Automatic feature learning for glaucoma detection based on deep learning. In: MICCAI 2015: 18th International conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18. Springer, pp 669–677
3. Diaz-Pinto A, Morales S, Naranjo V, Köhler T, Mossi JM, Navea A (2019) Cnns for automatic glaucoma assessment using fundus images: an extensive validation. Biomed Eng Online 18:1–19
4. Mahmud M, Kaiser MS, Hussain A, Vassanelli S (2018) Applications of deep learning and reinforcement learning to biological data. IEEE Trans Neural Netw Learn Syst 29(6):2063–2079. https://doi.org/10.1109/TNNLS.2018.2790388
5. Mahmud M, Kaiser MS, McGinnity TM, Hussain A (2021) Deep learning in mining biological data. Cognitive Comput 13:1–33
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