Explore projects
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repository for the photometric pipeline of the STELLA/WiFSIP telescope
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A machine learning library to detect solar spots on APPLAUSE solar plates: https://www.plate-archive.org/applause/
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Bash script to download the budget information from https://klr.aip.de.
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the extract features steps: this step uses the threshold method to identify pixels that may be part of a sunspots
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the label-features step: in this step the pixels that may be part of a sunspots are grouped in regions and each region is labeled as a feature, the number of feature per plate is computed on the fly.
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The select-meaningful-features step: in this step we set the meaningfulness of each plates, and of each feature
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The extract-features-properties step: in this step we compute the geometrical/morphological properties of each meaningful features
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The modern pipeline code (prototype). Provide a config file, it builds the pipeline, setups a traceable environment, and run the pipeline on a K8s cluster (assuming access to some PV).
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