Biomedical Signal Processing and Control, Journal Year: 2024, Volume and Issue: 100, P. 107040 - 107040
Published: Oct. 7, 2024
Language: Английский
Biomedical Signal Processing and Control, Journal Year: 2024, Volume and Issue: 100, P. 107040 - 107040
Published: Oct. 7, 2024
Language: Английский
Computer Systems and Information Technologies, Journal Year: 2024, Volume and Issue: 1, P. 27 - 32
Published: March 28, 2024
Diabetic retinopathy is a retinal disease caused by diabetes. The progression of this can lead to blindness. Every year, the number patients with increases. damage be slowed if it diagnosed early. article describes features creation neural network model and development system high accuracy rates for recognition diabetic retinopathy. advantages InceptionResNetv2 convolutional architecture are considered. This uses residual connections that help facilitate learning process. different methods reduce dimensionality feature map, making more economical in terms memory computation. has compared other networks. applied blood vessel segmentation eye images resolutions. In study, modification was carried out. use additional MaxPooling Dense layers improved speed network. Dropout layer effectively used prevent overtraining. determining degree origin implemented Python programming language. Model built using Keras library. Images from set EyePacs were processed cropping black frames Gaussian blur filter minimizing effect changing position images. During research, found 21 epochs needed achieve maximum accuracy. program calculates probability an image belonging certain class rate 1 98.6%, 2 - 98.5%, 3 98.3%, 4 98.15%, 5 98.1%.
Language: Английский
Citations
0Lecture notes in networks and systems, Journal Year: 2024, Volume and Issue: unknown, P. 83 - 92
Published: Jan. 1, 2024
Language: Английский
Citations
0Biomedical Signal Processing and Control, Journal Year: 2024, Volume and Issue: 100, P. 107040 - 107040
Published: Oct. 7, 2024
Language: Английский
Citations
0