@inproceedings{dc4092a35e1349f7b2344b418f53fed4,
title = "Harnessing Machine Learning for interpersonal physical alignment",
abstract = "This work presents a novel way to determine interpersonal physical synchrony state by inspecting hands' postures obtained from a unique 3D depth camera device named Leap-Motion Controller. Several ML methods are utilized such as SVM, shallow feed-forward ANN and XGBoot. We show that even a simple ANN can outperform XgBoost in simple classification tasks.",
author = "Roi Yozevitch and Hila Gvirts and Ornit Apelboim and Elhanan Mishraky",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018 ; Conference date: 12-12-2018 Through 14-12-2018",
year = "2018",
month = jul,
day = "2",
doi = "10.1109/ICSEE.2018.8646075",
language = "الإنجليزيّة",
series = "2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "2018 IEEE International Conference on the Science of Electrical Engineering in Israel, ICSEE 2018",
address = "الولايات المتّحدة",
}