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Integrating AI Image Generation in Web Applications Using the MERN Stack and GANs

dc.contributor.advisorAdamkó, Attila Tamás
dc.contributor.authorElsawwaf, Mohamed Hesham Farouk Hassan
dc.contributor.departmentDE--Informatikai Kar
dc.date.accessioned2026-07-14T14:46:09Z
dc.date.available2026-07-14T14:46:09Z
dc.date.created2025-11-05
dc.description.abstractThe project delivers a full MERN-stack web application that lets users generate, share, and curate AI-created artwork. The React frontend organizes components for authentication, image generation, galleries, and profile management, with TailwindCSS ensuring a responsive interface. An Express/Node backend coordinates DALL-E image generation, and uses fluxcontext and runware, post management, social interactions, and authentication via Firebase, while MongoDB stores user and content data. Cloudinary provides external storage and delivery for generated images, reducing local overhead. Social features—likes, comments, favorites—and robust search across prompts, tags, and users deepen community engagement. Overall, the build emphasizes real-time AI integration, secure access control, and scalable content handling.
dc.description.courseProgramtervező informatikus
dc.description.degreeBSc/BA
dc.format.extent41
dc.identifier.urihttps://hdl.handle.net/2437/413137
dc.language.isoen
dc.rights.infoHozzáférhető a 2022 decemberi felsőoktatási törvénymódosítás értelmében.
dc.subjectrunware
dc.subjectmern stack
dc.subjectmongo db
dc.subjectreact
dc.subject.dspaceInformatics::Computer Science
dc.titleIntegrating AI Image Generation in Web Applications Using the MERN Stack and GANs

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