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Embedding-based real-time change point detection with application to activity segmentation in smart home time series data

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aitoralmeida/activity_segmentation

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Deep Learning for activity recognition, segmentation and behavior prediction

This repository contains the work done within the FuturAAL-Ego project. The repository contains the code for two of the main tasks. The code for behavior prediction can be foind in the next_action_prediction folder. The code for activity segmentation can be found in the segmentation folder.

Citation

If you are using this work, please include the following cite:

Bermejo, U., Almeida, A., Bilbao, A., & Azkune, G. (2021). Embedding-based real-time change point detection with application to activity segmentation in smart home time series data. Expert Systems with Applications, 115641.

Funding

This work was carried out with the financial support of FuturAAL-Ego (RTI2018-101045-A-C22) granted by Spanish Ministry of Science, Innovation and Universities.

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Embedding-based real-time change point detection with application to activity segmentation in smart home time series data

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