Tackling class imbalance in computer vision: a contemporary review
Class imbalance is a key issue affecting the performance of computer vision applications
such as medical image analysis, objection detection and recognition, image segmentation …
such as medical image analysis, objection detection and recognition, image segmentation …
[HTML][HTML] On the analyses of medical images using traditional machine learning techniques and convolutional neural networks
Convolutional neural network (CNN) has shown dissuasive accomplishment on different
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
areas especially Object Detection, Segmentation, Reconstruction (2D and 3D), Information …
Analysis of deep learning techniques for prediction of eye diseases: A systematic review
A Bali, V Mansotra - Archives of Computational Methods in Engineering, 2024 - Springer
The prediction and early diagnosis of eye diseases are critical for effective treatment and
prevention of vision loss. The identification of eye diseases has recently been the subject of …
prevention of vision loss. The identification of eye diseases has recently been the subject of …
[HTML][HTML] Using deep learning architectures for detection and classification of diabetic retinopathy
Diabetic retinopathy (DR) is a common complication of long-term diabetes, affecting the
human eye and potentially leading to permanent blindness. The early detection of DR is …
human eye and potentially leading to permanent blindness. The early detection of DR is …
[HTML][HTML] SSMD-UNet: semi-supervised multi-task decoders network for diabetic retinopathy segmentation
Diabetic retinopathy (DR) is a diabetes complication that can cause vision loss among
patients due to damage to blood vessels in the retina. Early retinal screening can avoid the …
patients due to damage to blood vessels in the retina. Early retinal screening can avoid the …
CRA-Net: Transformer guided category-relation attention network for diabetic retinopathy grading
F Zang, H Ma - Computers in Biology and Medicine, 2024 - Elsevier
Automated grading of diabetic retinopathy (DR) is an important means for assisting clinical
diagnosis and preventing further retinal damage. However, imbalances and similarities …
diagnosis and preventing further retinal damage. However, imbalances and similarities …
Graph adversarial transfer learning for diabetic retinopathy classification
J Hu, H Wang, L Wang, Y Lu - IEEE Access, 2022 - ieeexplore.ieee.org
Diabetic retinopathy (DR) is an essential factor that has caused vision loss and even
blindness in middle-aged and older adults. A system that can automatically perform DR …
blindness in middle-aged and older adults. A system that can automatically perform DR …
[HTML][HTML] Artificial intelligence for diabetic retinopathy detection: a systematic review
The incidence of diabetic retinopathy (DR) has increased at a rapid pace in recent years all
over the world. Diabetic eye illness is identified as one of the most common reasons for …
over the world. Diabetic eye illness is identified as one of the most common reasons for …
[HTML][HTML] Fine-grained attention & knowledge-based collaborative network for diabetic retinopathy grading
M Tian, H Wang, Y Sun, S Wu, Q Tang, M Zhang - Heliyon, 2023 - cell.com
Accurate diabetic retinopathy (DR) grading is crucial for making the proper treatment plan to
reduce the damage caused by vision loss. This task is challenging due to the fact that the …
reduce the damage caused by vision loss. This task is challenging due to the fact that the …
Enhancing deep learning pre-trained networks on diabetic retinopathy fundus photographs with SLIC-G
Diabetic retinopathy disease contains lesions (eg, exudates, hemorrhages, and
microaneurysms) that are minute to the naked eye. Determining the lesions at pixel level …
microaneurysms) that are minute to the naked eye. Determining the lesions at pixel level …