Age-Related Macular Degeneration Identification by the Application of Deep Convolutional Neural Network System
DOI:
https://doi.org/10.9734/bpi/acst/v6/6545BKeywords:
Age-related Macular Degeneration (AMD), Wet AMD (WAMD), Dry AMD (DAMD), Deep Convolutional Neural Network (CNN), RGB to Green conversion (RGB to G conversion), G image (Green image)Abstract
Age-related Macular Degeneration (AMD) is determined by using Deep Convolution Neural Network (CNN) for determining the suitability of using the transfer learning. There are over 420 images in this AMD collection. In the remaining absolutely linked layers, CNN with batch normalisation was also applied. The performance of a CNN that has been explicitly trained with a sufficient diversity of images outperforms that of a CNN that has been used. AMD identification and screening is carried out by using pre-training network. An image of the fundus was used to test the AMD. Normally, Wet AMD (WAMD), and Dry AMD (DAMD) are all medically significant. With accuracy of 100 percent, specificity of 100 percent, and sensitivity of 100 percent, we have improved our performance.
