• Shreetama Mohanta
• Ojaswa Sharma
• Prakash Ramachandran

In the rapidly evolving digital landscape, efficient and personalized restaurant websites are essential for enhancing customer experience and operational efficiency. This project presents an end-to-end AI solution for automating restaurant website design, leveraging fine-tuned Stable Diffusion models for advanced thematic image synthesis. The framework integrates AI techniques to generate customized visual elements, ensuring alignment with a restaurant's unique branding and style. It also employs seamless automation processes to streamline the generation of interactive and responsive website components. Through rigorous testing and iterative improvements, the solution demonstrates its effectiveness in reducing development time while maintaining high-quality design standards. This approach addresses critical challenges such as scalability, aesthetic consistency, and adaptability in website customization, marking a significant step forward in AI-powered web development for the restaurant industry.

AI-driven solutions, restaurant website design, Stable Diffusion, image synthesis, web automation.

"End-to-End AI Solution for Restaurant Website Design with Fine-Tuned Stable Diffusion Image Synthesis ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 11, page no.e720-e726, November-2024, Available :http://www.jetir.org/papers/JETIR2411481.pdf

"End-to-End AI Solution for Restaurant Website Design with Fine-Tuned Stable Diffusion Image Synthesis ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 11, page no. ppe720-e726, November-2024, Available at : http://www.jetir.org/papers/JETIR2411481.pdf