IRJET – International Research Journal of Engineering and Technology

UI Code Generation using Deep Learning

Proposed an end-to-end deep learning model that converts GUI screenshots into functional code, reducing manual interface implementation. The model leverages Convolutional Neural Networks (CNN) for visual feature extraction and Gated Recurrent Units (GRU) for sequence modeling to generate structured GUI code from image tokens.

Key Concepts: Deep Learning • CNN • GRU • Sequence Modeling • GUI Automation