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
Checkout the Usage section or the included Jupyter notebooks for a toy problem or the RFI problem discussed in the paper.
The code is not tied to a specific segmentation such that it can be 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.
