Repository logo
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
Repository logo
  • Communities & Collections
  • All of DSpace
  • English
  • Català
  • Čeština
  • Deutsch
  • Español
  • Français
  • Gàidhlig
  • Italiano
  • Latviešu
  • Magyar
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Suomi
  • Svenska
  • Türkçe
  • Tiếng Việt
  • Қазақ
  • বাংলা
  • हिंदी
  • Ελληνικά
  • Yкраї́нська
  • Log In
    New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Saman Mansoor, M.Abubakar Arshad and M. Safan Shahid"

Now showing 1 - 1 of 1
Results Per Page
Sort Options
  • Loading...
    Thumbnail Image
    Item
    Ocular Diseases Detection
    (UMT, Lahore, 2023) Saman Mansoor, M.Abubakar Arshad and M. Safan Shahid
    The most crucial sense organ for seeing the outside world is the eye. Some of the biggest issues with vision are ocular eye disorders. The most prevalent condition in this ocular eye illness is cataracts. A cataract is a cloudy condition that impairs vision in the eye and makes things hazy. It primarily exists in old people because of their age. The detection of ocular eye disorders is a somewhat challenging task for computer-aided diagnostics. The Ocular Disease Recognition app uses machine learning methods including convolution neural networks (CNN) and image pre processing to identify and diagnose common ocular disorders. The app is built using Flutter and utilizes a model trained on a dataset of ocular images to identify various diseases. The app provides a diagnosis as well as details on each condition's probable complications and available treatments. The app's objective is to improve patient and healthcare provider access to and effectiveness of eye illness diagnostics.

DSpace software copyright © 2002-2026 LYRASIS

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback