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Deep Learning in Retinal Image Segmentation and Feature Extraction: A Review
2021
International Journal of Online and Biomedical Engineering (iJOE)
Image recognition and understanding is considered as a remarkable subfield of Artificial Intelligence (AI). In practice, retinal image data have high dimensionality leading to enormous size data. As the morphological retinal image datasets can be analyzed in an expansive and non-invasive way, AI more precisely Deep Learning (DL) methods are facilitating in developing intelligent retinal image analysis tools. The most recently developed DL technique, Convolutional Neural Network (CNN) showed
doi:10.3991/ijoe.v17i14.24819
fatcat:3eeytz33xve6lgyawa6am5w5ly