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valeprado92/AeForGraph: AeForGraph

Authors: valeprado92;

valeprado92/AeForGraph: AeForGraph

Abstract

Spatio-temporal graph autoencoder for automated evaluation of human actions in 3D in immersive VR-based training for archaeologists This is the folder containing the scripts related to the paper "Spatio-temporal graph autoencoder for automated evaluation of human actions in 3D in immersive VR-based training for archaeologists". Some of them deal with preprocessing, and the structure of the main script indicates the order in which to run them. Finally, "variance_per_feature.py", "statistical_analysis.py", and "data_preprocessing.py" are not included in the pipeline because they are part of the preprocessing. "stream_and_response.py", on the other hand, is used to connect Unity to Python.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average