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semi-supervised-har

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The source of the solution of SHL recognition challenge 2019 based on Semi-supervised Adversarial Autoencoders (AAE) for Human Activity Recognition (HAR)

adversarial-autoencoders autoencoder deep-learning human-activity-recognition keras tensorflow

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Name		Name	Last commit message	Last commit date
timeseries		timeseries
LICENSE		LICENSE
README.md		README.md
cnn_aae_baseline.ipynb		cnn_aae_baseline.ipynb
environment.yaml		environment.yaml
plots_examples.ipynb		plots_examples.ipynb

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Semi-supervised HAR

The source of the solution of SHL recognition challenge 2019 based on Semi-supervised Adversarial Autoencoders (AAE) for Human Activity Recognition (HAR)

Paper: https://dl.acm.org/citation.cfm?id=3344854

Author's LinkedIn: https://www.linkedin.com/in/dmitrybalabka/

About

The source of the solution of SHL recognition challenge 2019 based on Semi-supervised Adversarial Autoencoders (AAE) for Human Activity Recognition (HAR)

adversarial-autoencoders autoencoder deep-learning human-activity-recognition keras tensorflow

8 stars

1 watching

Report repository

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