This is a generic convolutional neural network implementation following the U-Net architecture proposed in this paper written with Tensorflow. The code has been developed and used for Radio Frequency Interference mitigation using deep convolutional neural networks
Using tf_unet is easy! Checkout the Usage section or the included Jupyter notebooks for a toy problem or for a RFI problem.
The code is not tied to a specific segmentation such that it has been used in a toy problem to detect circles in a noisy image.
To more complex application such as the detection of radio frequency interference (RFI) in radio astronomy.
Or to detect galaxies and star in wide field imaging data.
