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1. Noise Estimation and Removal in Fundus Images Using Pyramid Real Image Denoising Network

2. Multiscale Color Guided Attention Ensemble Classifier for Age-Related Macular Degeneration Using Concurrent Fundus and Optical Coherence Tomography Images

3. Adaptive Class Learning to Screen Diabetic Disorders in Fundus Images of Eye

5. VISTA: vision improvement via split and reconstruct deep neural network for fundus image quality assessment.

6. A Dual-Modal Fusion Network Using Optical Coherence Tomography and Fundus Images in Detection of Glaucomatous Optic Neuropathy.

7. Assessing the Correlation Between Retinal Arteriolar Bifurcation Parameters and Coronary Atherosclerosis.

8. Diagnosis and multiclass classification of diabetic retinopathy using enhanced multi thresholding optimization algorithms and improved Naive Bayes classifier.

9. Assessing the Correlation Between Retinal Arteriolar Bifurcation Parameters and Coronary Atherosclerosis

10. Analysis of image features of fundus blood vessel in healthy human eye based on deep learning techniques

11. Validation of neuron activation patterns for artificial intelligence models in oculomics

12. Validation of neuron activation patterns for artificial intelligence models in oculomics.

13. Multi-classification of eye disease based on fundus images using hybrid Squeeze Net and LRCN model.

14. Evaluating the potential of retinal photography in chronic kidney disease detection: a review.

15. Automatic Exudate Detection from Retinal Fundus Images in Diabetic Retinopathy.

16. Modified 2D-EWT-based Automated System for Glaucoma Diagnosis.

17. Earlier smart prediction of diabetic retinopathy from fundus image under innovative ResNet optimization maneuver.

18. A Survey on Classifying Ocular Diseases Using Deep Learning and Machine Learning Techniques.

19. Effective automatic classification methods via deep learning for myopic maculopathy

20. Coarse-to-Fine Latent Diffusion Model for Glaucoma Forecast on Sequential Fundus Images

21. MM-Retinal: Knowledge-Enhanced Foundational Pretraining with Fundus Image-Text Expertise

22. HRDecoder: High-Resolution Decoder Network for Fundus Image Lesion Segmentation

23. Convolutional Neural Network Analysis for Glaucoma Detection in Retinal Image Analysis Compared with the K-Nearest Neighbors Algorithm’s Accuracy

25. Detection and Grading of Diabetic Retinopathy from Fundus Images by Applying Transfer Learning

27. FD-SDG: Frequency Dropout Based Single Source Domain Generalization Framework for Retinal Vessel Segmentation

28. A Vision Transformer Approach to Fundus Image Classification

29. Automatic Detection of Diabetic Retinopathy from Retinal Fundus Images Using MobileNet Model

30. Review Paper on Glaucoma Detection Using Machine Learning

31. Web Application for Early Cataract Detection Using a Deep Learning Cloud Service

33. Comparison of CNN and KNN Methods for Cataract Classification and Detection Based on Fundus Images

34. Eye Disease Classification Using VGG-19 Architecture

35. Utilising Deep Learning Techniques, Detect and Categorise Diabetic Retinopathy

36. Prediction of Spherical Equivalent with Vanilla ResNet

37. Beyond MobileNet: An Improved MobileNet for Retinal Diseases

38. Image-Based Retinal Haemodynamics Simulation of Healthy and Pathological Retinal Vasculature

39. Hybrid Deep Learning Framework for Glaucoma Detection Using Fundus Images

41. Automated Segmentation of Macula in Retinal Images Using Deep Learning Methodology

44. Hybrid technique for fundus image enhancement using modified morphological filter and denoising net.

45. An attention enriched encoder–decoder architecture with CLSTM and RES unit for segmenting exudate in retinal images.

46. 基于改进YOLOv5的眼底出血点检测算法.

47. UGLS: an uncertainty guided deep learning strategy for accurate image segmentation.

48. A systematic review on diabetic retinopathy detection and classification based on deep learning techniques using fundus images.

49. Assessment of retinal blood vessel segmentation using U-Net model: A deep learning approach

50. Evaluating the potential of retinal photography in chronic kidney disease detection: a review

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