An Improved Ensemble Extreme Learning Machine Classifier for Detecting Diabetic Retinopathy in Fundus Images
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-16364-7_26
Reference20 articles.
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2. Akram, M.U., Akbar, S., Hassan, T., Khawaja, S.G., Yasin, U., Basit, I.: Data on fundus images for vessels segmentation, detection of hypertensive retinopathy, diabetic retinopathy and papilledema. Data Brief 29, 105282 (2020)
3. Tsiknakis, N., et al.: Deep learning for diabetic retinopathy detection and classification based on fundus images: a review. Comput. Biol. Med. 135, 104599 (2021)
4. Ravishankar, S., Jain, A., Mittal, A.: Automated feature extraction for early detection of diabetic retinopathy in fundus images. In: 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp. 210–217. IEEE, June 2009
5. Bonaccorso, G.: Machine Learning Algorithms: Popular Algorithms for Data Science and Machine Learning. Packt Publishing Ltd. (2018)
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1. AHO-MLCNN: archerfish hunting optimisation based modified lightweight CNN for diabetic retinopathy detection;Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization;2023-06-27
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