id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
cana-6162	Shital.P.Mohite	A Unified Framework for High-Resolution Text-to-Image Generation Using Stable Diffusion with Adaptive Upscaling via Real-ESRGAN and EDSR	2025	11	.pdf	application/pdf	2905	151	36	Stable Diffusion's architecture, based on a latent diffusion process conditioned on CLIP- based text embeddings, represents a significant step forward in achieving a balance between image quality, generation speed, and accessibility, making it a widely adopted model for various text-to-image synthesis applications.2.2 Image Super-Resolution Image super-resolution (SR) is the task of upscaling low-resolution images to higher resolutions while recovering lost details and enhancing visual quality. We demonstrate the superiority, flexibility, and efficacy of this pipeline through experimental analysis, mathematical modelling, and visual comparisons Keywords— Latent Diffusion Models, Super-Resolution, Real- ESRGAN, EDSR, Text-to-Image Synthesis, Stable Diffusion, Image Upscaling Introduction Text-to-image generation is a cross-modal task that merges image creation and natural language recognition.	cache/cana-6162.pdf	txt/cana-6162.txt