Digital Repository

CodeCanvas: Automatic code generation from UI designs using Machine learning

Show simple item record

dc.contributor.author Fernando, Minoly Fernando
dc.date.accessioned 2025-06-12T05:23:37Z
dc.date.available 2025-06-12T05:23:37Z
dc.date.issued 2024
dc.identifier.citation Fernando, Minoly Fernando (2024) CodeCanvas: Automatic code generation from UI designs using Machine learning. BSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 2019444
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/2518
dc.description.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." en_US
dc.language.iso en en_US
dc.subject Automated code generation en_US
dc.subject UI-to-code conversion en_US
dc.subject Machine Learning en_US
dc.title CodeCanvas: Automatic code generation from UI designs using Machine learning en_US
dc.type Thesis en_US


Files in this item

This item appears in the following Collection(s)

Show simple item record

Search


Advanced Search

Browse

My Account