Cavity Detection Tool (CADET)
CADET is a machine learning pipeline trained for identification of surface brightness depressions (so-called X-ray cavities) on noisy Chandra images of early-type galaxies and galaxy clusters. The pipeline consists of a convolutional neural network trained for producing pixel-wise cavity predictions and a DBSCAN clustering algorithm, which decomposes the predictions into individual cavities. The pipeline is further described in Plšek et al. 2023.
How to use
from huggingface_hub import from_pretrained_keras
model = from_pretrained_keras("Plsek/CADET-v1")
y_pred = model.predict(X.reshape(1,128,128,1))
How to cite
The CADET pipeline was originally developed as a part of my diploma thesis and was further described in Plšek et al. 2023. If you use the CADET pipeline in your research, please cite the following paper:
@misc{plšek2023cavity,
title={CAvity DEtection Tool (CADET): Pipeline for automatic detection of X-ray cavities in hot galactic and cluster atmospheres},
author={Tomáš Plšek and Norbert Werner and Martin Topinka and Aurora Simionescu},
year={2023},
eprint={2304.05457},
archivePrefix={arXiv},
primaryClass={astro-ph.HE}
}
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