… In this study, we have developed four neural networkbased ocular disease, classification
models. Those models are Resnet-34, EfficientNet, MobileNetV2 and VGG-16. Out of which, the …

… detection model with Hybrid Neural Network. Bhowmik et al. [45] proposed a paper for the
eye disease prediction for early-stage detection … an AI-based algorithm for the detection of the …

… detection of eye disease at an early stage. We propose comprehensive age-related eye disease
detection at an early stage using … The flower pollination optimization algorithm was used …

… learning based models for fundus image classification. … performance of the proposed
algorithm are also discussed here. … learning based CNN for the detection of ocular diseases is …

… algorithms to classify multi-class DED automatically. Previous studies in this field found that
the new DL algorithms are ineffective in classifying … disease identification. Automated DED …

… neural network method accuracy on smaller feature subsets and for making a fairer comparison
on eye diseases detection and classification … convolutional neural network algorithms on …

… In Reference [26], a survey of various computer-based ocular disease identification …
classification algorithms that include decision tree, random forest, naïve Bayes and neural networks…

… of DL algorithms for categorizing eye diseases in contrast to … forward pass of a neural network
to detect and localize objects … [39] proposed DL-based ophthalmic disease detection. They …

… neural network was used to create an intelligent expert system for detecting the most serious
eye … The detection and accuracy of deep learning algorithms were both good. This method …

… disease stages, automatic and robust diagnosing algorithms … In respect to ocular disease
diagnosing, CNNs have shown … from disease classification to object detection. A pixel-wise …