Erica Ramirez, Markus Wimmer, Martin Atzmueller. A Computational Framework for Interpretable Anomaly Detection and Classification of Multivariate Time Series with Application to Human Gait Data Analysis. In Mar Marcos, Jose M. Juarez, Richard Lenz, Grzegorz J. Nalepa, Slawomir Nowaczyk, Mor Peleg, Jerzy Stefanowski, Gregor Stiglic, editors, Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems - AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26-29, 2019, Revised Selected Papers. Volume 11979 of Lecture Notes in Computer Science, pages 132-147, Springer, 2019. [doi]
@inproceedings{RamirezWA19,
title = {A Computational Framework for Interpretable Anomaly Detection and Classification of Multivariate Time Series with Application to Human Gait Data Analysis},
author = {Erica Ramirez and Markus Wimmer and Martin Atzmueller},
year = {2019},
doi = {10.1007/978-3-030-37446-4_11},
url = {https://doi.org/10.1007/978-3-030-37446-4_11},
researchr = {https://researchr.org/publication/RamirezWA19},
cites = {0},
citedby = {0},
pages = {132-147},
booktitle = {Artificial Intelligence in Medicine: Knowledge Representation and Transparent and Explainable Systems - AIME 2019 International Workshops, KR4HC/ProHealth and TEAAM, Poznan, Poland, June 26-29, 2019, Revised Selected Papers},
editor = {Mar Marcos and Jose M. Juarez and Richard Lenz and Grzegorz J. Nalepa and Slawomir Nowaczyk and Mor Peleg and Jerzy Stefanowski and Gregor Stiglic},
volume = {11979},
series = {Lecture Notes in Computer Science},
publisher = {Springer},
isbn = {978-3-030-37446-4},
}