EscVM/RAMS
Official TensorFlow code for paper "Multi-Image Super Resolution of Remotely Sensed Images Using Residual Attention Deep Neural Networks".
- Stars
- 94
- Forks
- 22
- Open issues
- 6
- Last push
- 9mo ago
About RAMS
RAMS is a free, open-source computer vision tool by EscVM, written mainly in Jupyter Notebook. Official TensorFlow code for paper "Multi-Image Super Resolution of Remotely Sensed Images Using Residual Attention Deep Neural Networks". It has 94 GitHub stars and 22 forks, and was last updated 9mo ago. It's released under the Apache-2.0 license, a standard open-source license.
- License
- Apache-2.0
- Language
- Jupyter Notebook
- Stars
- 94
- Last update
- 9mo ago
- Runs on Mac
- Not stated
- GPU
- Not stated
- Paid API key
- Not stated
- Self-hostable
- Not stated
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RAMS FAQ
Is RAMS free?
Yes. RAMS is open source and free to use. It's released under the Apache-2.0 license, a standard open-source license.
Does RAMS run on a Mac?
The project doesn't say. Check its installation guide before you start.
Does RAMS need a GPU?
The project doesn't state hardware needs. AI models generally run much faster with a GPU.
Is RAMS still maintained?
It was last updated 9mo ago. Check recent issues on GitHub to judge how active it is.
What are alternatives to RAMS?
Similar free, open-source tools include deep-learning-drizzle, supervision, ultralytics, label-studio.