Detection of Exudates in Fundus Photographs using Convolutional Neural Networks (CROSBI ID 633948)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
Prentašić, Pavle ; Lončarić, Sven
engleski
Detection of Exudates in Fundus Photographs using Convolutional Neural Networks
Diabetic retinopathy is one of the leading causes of preventable blindness in the developed world. Early diagnosis of diabetic retinopathy enables timely treatment and in order to achieve it a major effort will have to be invested into screening programs and especially into automated screening programs. Detection of exudates is very important for early diagnosis of diabetic retinopathy. Deep neural networks have proven to be a very promising machine learning technique, and have shown excellent results in different compute vision problems. In this paper we show that convolutional neural networks can be effectively used in order to detect exudates in color fundus photographs.
diabetic retinopathy; machine learning; deep learning; convolutional neural networks; image analysis
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Podaci o prilogu
188-192.
2015.
objavljeno
Podaci o matičnoj publikaciji
ISPA 2015 (9th International Symposium on Image and Signal Processing and Analysis)
Zagreb:
Podaci o skupu
9th International Symposium on Image and Signal Processing and Analysis
predavanje
07.09.2015-09.09.2015
Zagreb, Hrvatska