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@article{193735,
        author = {Dr. C. Siva Balaji Yadav and C R Sai Dheekshitha and Bellapukonda Narasimha Naidu and Mangapuram Sai Dhiraj Kumar and Donthireddy Siva Sankar Reddy},
        title = {TEXT-TO-IMAGE GENERATION FOR ENHANCED WEB UI DEVELOPMENT},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {10},
        pages = {2328-2337},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=193735},
        abstract = {The design of effective web user interfaces (UI) traditionally depends on professional designers or pre-built image resources, which increases development time and cost. This project presents a text-to-image generation–based system for enhanced web UI development that automates the creation of visual content using deep learning techniques. The proposed system employs a pre-trained Stable Diffusion model to generate high-quality images from user-provided textual descriptions. Secure user authentication and administrative modules are incorporated to manage system access and functionality. The system is capable of generating multiple visual styles, including photorealistic and cinematic images, Alegria-style illustrations, and black silhouette icon-style graphics, making it suitable for diverse web UI requirements. Experimental evaluation demonstrates that the automated image generation process significantly reduces manual design effort, frontend development time, and reliance on external image repositories. The results confirm that text-to-image generation is an effective and scalable approach for improving efficiency, flexibility, and visual quality in modern web UI development.},
        keywords = {Text-to-image generation, Stable Diffusion, Generative AI, Web UI development, Diffusion models, Automated design, Deep learning, Human–computer interaction},
        month = {March},
        }