SaumyaBhandari/Image-SuperResolution-
A Super Sampling model created using the SRCNN method proposed by Chao Dong, Chen Change Loy in 2015. It uses Convolutional Networks to identify features and uses "Depth-To-Feature" technique in the end to generate a high resolution image of a given low resolution input. The model is trained and tested on BSDS500 dataset.
No commits in the last 6 months.
Stars
2
Forks
—
Language
Jupyter Notebook
License
—
Category
Last pushed
May 14, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/SaumyaBhandari/Image-SuperResolution-"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Higher-rated alternatives
HasnainRaz/Fast-SRGAN
A Fast Deep Learning Model to Upsample Low Resolution Videos to High Resolution at 30fps
NatLabRockies/sup3r
The Super-Resolution for Renewable Resource Data (sup3r) software uses generative adversarial...
the-database/traiNNer-redux
Deep learning training framework for image super resolution and restoration.
eugenesiow/super-image
Image super resolution models for PyTorch.
movehand/raisr
A Python implementation of RAISR