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Discrimination of retinal images containing bright lesions using sparse coded features and SVM., , и . Comput. Biol. Medicine, (2015)Tackling the Problem of Data Imbalancing for Melanoma Classification., , , , , , и . BIOIMAGING, стр. 32-39. SciTePress, (2016)Special Section Guest Editorial: Special Section on Quality Control by Artificial Vision: Nonconventional Imaging Systems., и . J. Electronic Imaging, 24 (6): 061101 (2015)Classification of melanoma lesions using sparse coded features and random forests., , , , , , , и . Medical Imaging: Computer-Aided Diagnosis, том 9785 из SPIE Proceedings, стр. 97850C. SPIE, (2016)Adaptive Feature Selection for Object Tracking with Particle Filter., , , и . ICIAR (2), том 8815 из Lecture Notes in Computer Science, стр. 395-402. Springer, (2014)Tackling the Problem of Data Imbalancing for Melanoma Classification., , , , , , и . BIOIMAGING, стр. 32-39. SciTePress, (2016)Retinal Fundus Multi-Disease Image Dataset (RFMiD): A Dataset for Multi-Disease Detection Research., , , , , , , , и . Data, 6 (2): 14 (2021)Automatic segmentation of tumors and affected organs in the abdomen using a 3D hybrid model for computed tomography imaging., , и . Comput. Biol. Medicine, (2020)Localization of optic disc and fovea in retinal images using intensity based line scanning analysis., , , , и . Comput. Biol. Medicine, (2017)Joint network for specular highlight detection and adversarial generation of specular-free images trained with polarimetric data., , , , и . Neurocomputing, (ноября 2023)