Deep learning methods, such as the Mobile net, CNN algorithm, and VGG 16 models, will be applied in the proposed model. People will benefit from the suggested method by being able to recognize and anticipate cataracts. Keywords: Convolutional neural network (CNN), Deep learning, VGG-16, and Mobile Net.

Abstract— Cataract refers to the opacification of the ocular lens, resulting in a decline in visual acuity. The current systems have undergone training using a limited dataset, resulting in the issue of overfitting. The suggested approach aims to utilise neural

Jul 17, 2023 · This paper presents an eye cataract detection system using Deep Convolution Neural Network (DCNNs) comprising two modules: training and testing.

Mar 10, 2024 · Android app which uses Neural architecture to detect the type and grade of the cataract. Deep learning project for ocular eye disease classification. Enhancing cataract detection using a MEDNet-based model. Improved accuracy …

Dec 8, 2022 · 2.2 Cataract detection using deep learning methods. The utilization of deep learning has demonstrated its capability to automatically extract features and overcome limitations in the field of cataract classification and grading.

Sep 15, 2021 · In this paper, a novel deep neural network, namely CataractNet, is proposed for automatic cataract detection in fundus images. The loss and activation functions are tuned to train the network with small kernels, fewer training parameters, and layers.

Jun 27, 2023 · This study proposes an automatic method for detecting and classifying cataracts in their earliest stages by combining a deep learning (DL) model with the 2D-discrete Fourier transform (DFT) spectrum of fundus images.

Jul 19, 2023 · In this study, a novel 16-layer deep learning neural network architecture is introduced for cataract detection. The proposed network aims to accurately identify the presence of cataracts 5 C-NN model including VGG16, VGG19 and Res Net-50 have been used to compare and show the effectiveness of our suggested model.

showcases the use of Convolutional Neural Network (CNN) deep learning models on color pictures of the retinal fundus to detect, identify, and classify cataracts. Three hundred normal photos and one hundred cataract images make up a set of four hundred color

In this project, we have Implemented a Cataract detection system using Convolutional Neural Networks. This neural network consists of 16 layers out of which 8 layers are used for feature extraction while the rest of the 8 layers are used for classification.