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Strided U-Net Model: Retinal Vessels Segmentation using Dice Loss., , , , , and . DICTA, page 1-8. IEEE, (2018)Identification of noise in the fundus images., , , , and . ICCSCE, page 191-196. IEEE, (2013)Neural network based denoised methods for retinal fundus images and MRI brain images., and . IJCNN, page 1151-1157. IEEE, (2016)An Improved Infrared and Visible Image Fusion Using an Adaptive Contrast Enhancement Method and Deep Learning Network with Transfer Learning., , , , , and . Remote. Sens., 14 (4): 939 (2022)Impact of ICA-Based Image Enhancement Technique on Retinal Blood Vessels Segmentation., , , , , and . IEEE Access, (2018)Automatic retinal vessel extraction algorithm based on contrast-sensitive schemes., , , , , and . IVCNZ, page 1-5. IEEE, (2016)Automatic Retinal Vessel Extraction Algorithm., , , , , and . DICTA, page 1-8. IEEE, (2016)Contrast normalization steps for increased sensitivity of a retinal image segmentation method., , , , and . Signal Image Video Process., 11 (8): 1509-1517 (2017)Optimized Brain Tumor Detection: A Dual-Module Approach for MRI Image Enhancement and Tumor Classification., , , , , and . IEEE Access, (2024)An Active Contour Method Based on Regularized Kernel Fuzzy C-Means Clustering., , , , and . IEEE Access, (2021)