Mobile activity recognition for a whole day-Reference-Cited by-同舟云学术

Mobile activity recognition for a whole day

Published:2015 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2015 ACM International Joint Conference on Pervasive and Ubiquitous Computing - UbiComp '15
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Author:

Inoue Sozo¹,Ueda Naonori²,Nohara Yasunobu³,Nakashima Naoki³

Affiliation:

1. Kyushu Institute of Technology, Tobata-ku, Kitakyushu, Japan

2. NTT Communication Science Laboratories, Seika, Sagara-gun, Kyoto, Japan

3. Kyushu University Hospital, Maidashi, Higashi-ku, Fukuoka, Japan

Funder

Japan Society for the Promotion of Science

Publisher

ACM Press

Reference53 articles.

1. Bao, L., and Intille, S. S.Pervasive Computing, vol. 3001 ofLecture Notes in Computer Science. Springer Berlin Heidelberg, Berlin, Heidelberg, 2004.

2. Chavarriaga, R., Sagha, H., Calatroni, A., Digumarti, S. T., Troster, G., Millan, J. D. R., and Roggen, D. The Opportunity challenge: A benchmark database for on-body sensor-based activity recognition.Pattern Recognition Letters 34(2013), 2033--2042.

3. Chen, L., Hoey, J., Nugent, C. D., Cook, D. J., and Yu, Z. Sensor-based activity recognition, 2012.

4. Collobert, R., Weston, J., Bottou, L., Karlen, M., Kavukcuoglu, K., and Kuksa, P. Natural Language Processing (almost) from Scratch.Journal of Machine Learning Research 12(2011), 2493--2537.

5. Damas, M., Rojas, I., Amft, O., Toth, A. M., Baños, O., Pomares, H., and Tóth, M. A. A benchmark dataset to evaluate sensor displacement in activity recognition. InProceedings of the 2012 ACM Conference on Ubiquitous Computing - UbiComp '12(2012), 1026.

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