Abstract:
"In software development, a major challenge has been the manual and error-prone process of
translating UI designs into functional code. This gap between design and implementation
consumes valuable time and introduces inconsistencies, leading to user frustration and higher development costs. As the demand for user-centric applications grows, bridging this gap has become essential.
To address this, an automated system using Convolutional Neural Networks (CNN) was developed to convert UI sketches into HTML and CSS code. The CNN model was designed to detect and classify UI elements within sketches, using layers configured to enhance feature extraction and accuracy. This approach ensured efficient and accurate interpretation of UI sketches, resulting in functional code generation."
