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Novel Example-Based Method for Super-Resolution and Denoising of Medical Images., , , , , and . IEEE Trans. Image Processing, 23 (4): 1882-1895 (2014)An effective example-based learning method for denoising of medical images corrupted by heavy Gaussian noise and poisson noise., , , , , , and . ICIP, page 823-827. IEEE, (2014)Adaptive Medical Image Denoising Using Support Vector Regression., , , , and . CAIP (1), volume 6854 of Lecture Notes in Computer Science, page 494-502. Springer, (2011)Towards an automated classification method for ureteroscopic kidney stone images using ensemble learning., , , , , , , , and . EMBC, page 1936-1939. IEEE, (2020)Dense Optical Flow for the Reconstruction of Weakly Textured and Structured Surfaces: Application to Endoscopy., , , , and . ICIP, page 310-314. IEEE, (2019)Assessing deep learning methods for the identification of kidney stones in endoscopic images., , , , , , , , , and 1 other author(s). EMBC, page 2778-2781. IEEE, (2021)Dilated Residual Convolutional Neural Networks for Low-Dose CT Image Denoising., , , , and . APCCAS, page 189-192. IEEE, (2020)Mosaicing of Images with Few Textures and Strong Illumination Changes: Application to Gastroscopic Scenes., , , and . ICIP, page 1263-1267. IEEE, (2018)A general form of illumination-invariant descriptors in variational optical flow estimation., , and . ICIP, page 2533-2537. IEEE, (2017)Medical image denoising using Kernel Ridge Regression., , , , and . ICIP, page 1597-1600. IEEE, (2011)