A survey on deep-learning-based diabetic retinopathy classification
The number of people who suffer from diabetes in the world has been considerably
increasing recently. It affects people of all ages. People who have had diabetes for a long …
increasing recently. It affects people of all ages. People who have had diabetes for a long …
Finding correlation between diabetic retinopathy and diabetes during pregnancy based on computer-aided diagnosis: a review
Diabetic retinopathy (DR) is a condition that damages the retina in people with diabetes and
can lead to vision loss. It can be detected by observing the morphological changes in the …
can lead to vision loss. It can be detected by observing the morphological changes in the …
Vision transformer model for predicting the severity of diabetic retinopathy in fundus photography-based retina images
Diabetic Retinopathy (DR) is a result of prolonged diabetes with poor blood sugar
management. It causes vision problems and blindness due to the deformation of the human …
management. It causes vision problems and blindness due to the deformation of the human …
Smart grading of diabetic retinopathy: an intelligent recommendation-based fine-tuned EfficientNetB0 framework
V Anand, D Koundal, WY Alghamdi… - Frontiers in Artificial …, 2024 - frontiersin.org
Diabetic retinopathy is a condition that affects the retina and causes vision loss due to blood
vessel destruction. The retina is the layer of the eye responsible for visual processing and …
vessel destruction. The retina is the layer of the eye responsible for visual processing and …
A novel transformer model with multiple instance learning for diabetic retinopathy classification
Y Yang, Z Cai, S Qiu, P Xu - IEEE Access, 2024 - ieeexplore.ieee.org
Diabetic retinopathy (DR) is an irreversible fundus retinopathy. A deep learning-based
automated DR diagnosis system can save diagnostic time. While Transformer has shown …
automated DR diagnosis system can save diagnostic time. While Transformer has shown …
Taotf: A two-stage approximately orthogonal training framework in deep neural networks
T Cui, J Li, Y Dong, L Liu - ECAI 2023, 2023 - ebooks.iospress.nl
The orthogonality constraints, including the hard and soft ones, have been used to
normalize the weight matrices of Deep Neural Network (DNN) models, especially the …
normalize the weight matrices of Deep Neural Network (DNN) models, especially the …
Vision transformer with masked autoencoders for referable diabetic retinopathy classification based on large-size retina image
Y Yang, Z Cai, S Qiu, P Xu - Plos one, 2024 - journals.plos.org
Computer-aided diagnosis systems based on deep learning algorithms have shown
potential applications in rapid diagnosis of diabetic retinopathy (DR). Due to the superior …
potential applications in rapid diagnosis of diabetic retinopathy (DR). Due to the superior …
Machine learning & deep learning algorithm reviews for diabetic retinopathy detection
P Hatode, MM Edinburgh - 2022 5th International Conference …, 2022 - ieeexplore.ieee.org
An artificial neural network, expressed as (ANN) a very popular algorithm in machine
learning, developed from artificial neurons, has less computation capability, and so is less …
learning, developed from artificial neurons, has less computation capability, and so is less …
A Novel Transformer Method Pretrained With Masked Autoencoders And Fractal Dimension For Diabetic Retinopathy Classification
Y Yang, Z Zha, C Zhou, L Zhang, S Qiu, P Xu - Fractals, 2024 - World Scientific
Diabetic retinopathy (DR) is one of the leading causes of blindness in a significant portion of
the working population, and its damage on vision is irreversible. Therefore, rapid diagnosis …
the working population, and its damage on vision is irreversible. Therefore, rapid diagnosis …
PMP-Swin: Multi-Scale Patch Message Passing Swin Transformer for Retinal Disease Classification
Retinal disease is one of the primary causes of visual impairment, and early diagnosis is
essential for preventing further deterioration. Nowadays, many works have explored …
essential for preventing further deterioration. Nowadays, many works have explored …