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Super Resolution

Developed by keras-io
This model is trained based on the Keras tutorial and can enhance low-resolution images to high-resolution images.
Image EnhancementOpen Source License:MIT#Sub-pixel convolution#Residual block enhancement#3x upscaling
Downloads 21
Release Time : 3/2/2022

Model Overview

This is an image super-resolution model that combines residual blocks with an efficient sub-pixel network, capable of converting 100x100 input images into 300x300 high-resolution images.

Model Features

Efficient Sub-pixel Network
Uses an efficient sub-pixel network to achieve image super-resolution and improve image quality.
Residual Block Structure
Incorporates residual block structures to enhance model training effectiveness and image restoration capabilities.
Fixed Size Processing
Supports 100x100 input images and outputs 300x300 high-resolution images.

Model Capabilities

Image super-resolution
Low-resolution image enhancement

Use Cases

Image Processing
Low-resolution Image Enhancement
Converts low-resolution images into high-resolution images to improve image quality.
Outputs a 300x300 high-resolution image.
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