A Novel Blood Vessel Parameter Extraction for Diabetic Retinopathy Detection
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-4676-9_45
Reference11 articles.
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2. V. Zeljković, M. Bojic, C. Tameze, V. Valev, in Classification Algorithm of Retina Images of Diabetic Patients Based on Exudates Detection. Proceedings of the 2012 International Conference on High Performance Computing and Simulation, HPCS 2012. 167–173 (2012). https://doi.org/10.1109/HPCSim.2012.6266907
3. B. Antal, A. Hajdu, An ensemble-based system for automatic screening of diabetic retinopathy. Knowl.-Based Syst. 60, 20–27 (2014). https://doi.org/10.1016/j.knosys.2013.12.023
4. E.V. Carrera, A. Gonzalez, R. Carrera, in Automated Detection of Diabetic Retinopathy Using SVM. Proceedings of the 2017 IEEE 24th International Congress on Electronics, Electrical Engineering and Computing, INTERCON 2017 (2017). https://doi.org/10.1109/INTERCON.2017.8079692
5. S. Wan, Y. Liang, Y. Zhang, Deep convolutional neural networks for diabetic retinopathy detection by image classification. Comput. Electr. Eng. 72, 274–282 (2018). https://doi.org/10.1016/j.compeleceng.2018.07.042
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