Nahiduzzaman, MdIslam, Md RobiulIslam, S. M.RiazulGoni, Md Omaer FaruqAnower, Md ShamimKwak, Kyung Sup2023-10-032023-10-032021-11-08Nahiduzzaman, M, Islam, M R, Islam, S M R, Goni, M O F, Anower, M S & Kwak, K S 2021, 'Hybrid CNN-SVD Based Prominent Feature Extraction and Selection for Grading Diabetic Retinopathy Using Extreme Learning Machine Algorithm', IEEE Access, vol. 9, pp. 152261-152274. https://doi.org/10.1109/ACCESS.2021.31257912169-3536ORCID: /0000-0003-2968-9561/work/144004111https://hdl.handle.net/2164/21825Funding Information: This work was supported in part by the National Research Foundation of Korea-Grant funded by the Government of Korea (Ministry of Science and ICT) under Grant NRF-2020R1A2B5B02002478, and in part by Sejong University through the Faculty Research Program under Grant 20212023142234620engSDG 3 - Good Health and Well-beingBen Graham's pre-processingcontrast limited adaptive histogram equalization (CLAHE)convolutional neural network-singular value decomposition (CNN-SVD)diabetic retinopathy (DR)extreme learning machine (ELM)QA75 Electronic computers. Computer scienceGeneral Computer ScienceGeneral Materials ScienceGeneral EngineeringQA75Journal article10.1109/ACCESS.2021.3125791http://www.scopus.com/inward/record.url?scp=85120352105&partnerID=8YFLogxK9