FSRCNN is a lightweight super-resolution network that accelerates single-image upscaling by performing feature extraction and reconstruction directly in the low-resolution space, significantly reducing computational cost compared to earlier approaches.
This model uses the FSRCNN ×4 variant, which is trained to reconstruct a high-resolution image at four times the input resolution. It is well suited for applications such as image enhancement, video upscaling, surveillance imagery, and edge devices where fast super-resolution inference is required.
