Improving the accuracy of diabetes retinopathy image classification using augmentation-Reference-Cited by-同舟云学术

Improving the accuracy of diabetes retinopathy image classification using augmentation

Published:2020-09-11 Issue: Volume: Page:
ISSN:
Container-title:Conference of the South African Institute of Computer Scientists and Information Technologists 2020
language:
Short-container-title:

Author:

Maistry Aleshan¹,Pillay Anban²,Jembere Edgar²

Affiliation:

1. University of KwaZulu-Natal, South Africa

2. University of KwaZulu-Natal, Centre for Artificial Intelligence Research, Council for Scientific and Industrial Research, South Africa

Publisher

ACM

Reference27 articles.

1. Automated Early Detection of Diabetic Retinopathy

2. Multiclass SVM-based automated diagnosis of diabetic retinopathy

3. An Ensemble-Based System for Microaneurysm Detection and Diabetic Retinopathy Grading

4. Paula Branco Luís Torgo and Rita P. Ribeiro. 2015. A Survey of Predictive Modelling under Imbalanced Distributions. CoRR abs/1505.01658(2015). arxiv:1505.01658http://arxiv.org/abs/1505.01658 Paula Branco Luís Torgo and Rita P. Ribeiro. 2015. A Survey of Predictive Modelling under Imbalanced Distributions. CoRR abs/1505.01658(2015). arxiv:1505.01658http://arxiv.org/abs/1505.01658

5. Uday Kiran Challa Pavankumar Yellamraju and Jignesh S. Bhatt. 2019. A Multi-class Deep All-CNN for Detection of Diabetic Retinopathy Using Retinal Fundus Images. In Pattern Recognition and Machine Intelligence Bhabesh Deka Pradipta Maji Sushmita Mitra Dhruba Kumar Bhattacharyya Prabin Kumar Bora and Sankar Kumar Pal (Eds.). Springer International Publishing Cham 191–199. Uday Kiran Challa Pavankumar Yellamraju and Jignesh S. Bhatt. 2019. A Multi-class Deep All-CNN for Detection of Diabetic Retinopathy Using Retinal Fundus Images. In Pattern Recognition and Machine Intelligence Bhabesh Deka Pradipta Maji Sushmita Mitra Dhruba Kumar Bhattacharyya Prabin Kumar Bora and Sankar Kumar Pal (Eds.). Springer International Publishing Cham 191–199.

Cited by 7 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Smart grading of diabetic retinopathy: an intelligent recommendation-based fine-tuned EfficientNetB0 framework;Frontiers in Artificial Intelligence;2024-04-16

2. CTNet: convolutional transformer network for diabetic retinopathy classification;Neural Computing and Applications;2023-12-19

3. Comparative Analysis of Diabetic Retinopathy Classification Approaches Using Machine Learning and Deep Learning Techniques;Archives of Computational Methods in Engineering;2023-09-20

4. Deep Learning with Heuristic Optimization Driven Diabetic Retinopathy Detection on Fundus Images;2023 2nd International Conference on Applied Artificial Intelligence and Computing (ICAAIC);2023-05-04

5. A deep learning nomogram of continuous glucose monitoring data for the risk prediction of diabetic retinopathy in type 2 diabetes;Physical and Engineering Sciences in Medicine;2023-04-11