Joint ordinal regression and multiclass classification for diabetic retinopathy grading with transformers and CNNs fusion network

L Ma, Q Xu, H Hong, Y Shi, Y Zhu, L Wang - Applied Intelligence, 2023 - Springer
Diabetic retinopathy (DR) is a chronic complication of diabetes that damages the retinal
blood vessels, leading to impaired vision and even blindness, and is one of the top three …

[HTML][HTML] A strip steel surface defect salient object detection based on channel, spatial and self-attention mechanisms

Y Sun, S Geng, H Guo, C Zheng, L Zhang - Electronics, 2024 - mdpi.com
Strip steel is extensively utilized in industries such as automotive manufacturing and
aerospace due to its superior machinability, economic benefits, and adaptability. However …

Triple-attentions based salient object detector for strip steel surface defects

L Zhang, X Li, Y Sun, H Guo - Scientific Reports, 2025 - nature.com
Accurate detection of surface defects on strip steel is essential for ensuring strip steel
product quality. Existing deep learning based detectors for strip steel surface defects …

A multi-modal multi-branch framework for retinal vessel segmentation using ultra-widefield fundus photographs

Q Xie, X Li, Y Li, J Lu, S Ma, Y Zhao… - Frontiers in Cell and …, 2025 - frontiersin.org
Background Vessel segmentation in fundus photography has become a cornerstone
technique for disease analysis. Within this field, Ultra-WideField (UWF) fundus images offer …

Hard Exudates Segmentation in Diabetic retinopathy using DiaRetDB1

M Yinghua, Y Heng, R Amarnath, Z Hui - IEEE Access, 2024 - ieeexplore.ieee.org
Diabetic retinopathy (DR) poses a major challenge in vision care, often leading to partial or
complete limited vision in adults. Early and accurate detection of DR is essential for timely …

Automatic multi-disease classification on retinal images using multilevel glowworm swarm convolutional neural network

R Chavan, D Pete - Journal of Engineering and Applied Science, 2024 - Springer
In ophthalmology, early fundus screening is an economical and effective way to prevent
blindness from eye diseases. Because clinical evidence does not exist, manual detection is …

DP-ProtoNet: An interpretable dual path prototype network for medical image diagnosis

L Kong, L Gong, G Wang, S Liu - 2023 IEEE 22nd International …, 2023 - ieeexplore.ieee.org
The significant success of deep learning has sparked interest in its application in medical
diagnosis. Some deep learning models have achieved expert-level accuracy on some …

Early Diagnosis of Cataract and Diabetic Retinopathy for Rural India using a Cloud-Based Deep Learning Model

N Vora, V Iyer, H Dalvi - 2023 International Conference on …, 2023 - ieeexplore.ieee.org
Diabetic retinopathy and cataract are the most prevalent causes of vision loss and blindness
in India's rural areas, where access to treatment is limited. The use of neural networks for the …

Design of an Iterative Method for Enhanced Retinal Image Analysis Using Stacked Deep Learning Operations

JS Mohan, LK Vishwamitra - Journal of Electrical Systems, 2024 - search.proquest.com
The necessity for advanced diagnostic techniques in ophthalmology has become
increasingly evident, particularly for conditions such as glaucoma and diabetic retinopathy …

Efficient Heart Disease Risk Management: A CNN-based Approach for Automated Prediction using Retinal Fundus Image

U Gawande, A Jadhao, O Bhalerao… - 2024 1st …, 2024 - ieeexplore.ieee.org
Despite established risk factors such as diabetes, heart disease remains a major health
problem. Early diagnosis of heart disease is essential for successful prevention and …