DRDUCV-case study

Job Description:

The main objective of this method is to detect DR(Diabetic Retinopathy) eye disease using Image Processing techniques.

Automating the process using Convolutional neural networks to speed up blindness detection in patients before its too late. Eye retina images contain artifacts, some of them are out of focus, underexposed, or overexposed etc. Also, some of the images have low brightness and low lightning conditions thus making it difficult to assess the difference between the images. First we do image preprocessing by applying Gaussian blur to bring out distinctive features in the images. In Gaussian Blur operation, the image is convolved with a Gaussian filter which is a

low-pass filter that removes the high-frequency components . Then convert the RGB scale images to Gray scale images and circular cropping from gray scale images is used. After applying some image augmentation, model

architecture is used. planning to use VGG-16

Навыки: PHP, Python, Исследования

О клиенте:
( 0 отзыв(-а, -ов) ) India

ID проекта: #36280856

7 фрилансеров(-а) готовы выполнить эту работу в среднем за ₹6214


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