Original title: Detection of Diabetic Retinopathy using Deep Learning and Transfer Learning Techniques with Oversampling to Address Imbalanced Dataset
Authors: RANĐELOVIĆ, Teodora
Document type: Bachelor's theses
Year: 2023
Language: eng
Abstract: The study aims to develop a system for detecting diabetic retinopathy using deep learning. In this study I have explored transfer learning with four distinct models and addressed the issue of an unbalanced dataset with oversampling. The final experiment achieved a significant improvement in accuracy and quadratic kappa score. The study highlights the potential of deep learning and the importance of addressing dataset imbalances for accurate results.
Keywords: accuracy; comparative analysis; Convolutional neural network; Deep learning; diabetic macular edema; Diabetic Retinopathy; Image classification; medical imaging; oversampling; quadratic kappa score; retinal fundus photographs; Transfer learning
Citation: RANĐELOVIĆ, Teodora. Detection of Diabetic Retinopathy using Deep Learning and Transfer Learning Techniques with Oversampling to Address Imbalanced Dataset. České Budějovice, 2023. bakalářská práce (Bc.). JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH. Přírodovědecká fakulta

Institution: University of South Bohemia in České Budějovice (web)
Document availability information: Fulltext is available in the Digital Repository of University of South Bohemia.
Original record: http://www.jcu.cz/vskp/72690

Permalink: http://www.nusl.cz/ntk/nusl-533596


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Universities and colleges > Public universities > University of South Bohemia in České Budějovice
Academic theses (ETDs) > Bachelor's theses