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Title
تشخیص دیابت با تصاویر شبکیه چشم با استفاده از یادگیری عمیق
Type of Research Thesis
Keywords
تشخیص دیابت ،رتینوپاتی،یادگیری عمیق ،تصاویر اسکن قرنیه
Abstract
Diagnosing diabetes at an early stage is critical to finding an effective treatment. Diabetes classification is implemented using a deep neural network, i.e., convolutional neural network, in the current work. dataset contains more than 410 images based on the retina for diabetes classification. number of training epochs was kept short of ensuring that the approach could be quickly used on any mobile device. experimental results suggest that the proposed deep learning model is effective and accurate. model has achieved an accuracy greater than 95%. model for determining all probable complications, including an orderly sequence in terms of the percentage of complications that can occur, will be improved in a future study as well. Additionally, deep learning algorithms and methodologies can be incorporated to enhance the work for an automated diabetes analysis.
Researchers (Student)، Hamed Alizadeh Ghazijahani (Primary Advisor)، Reza Zaker (Advisor)