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Comparing Gaussian Mixture Model and Hidden Markov Model to Classify Unique Physical Activities from Accelerometer Sensor Data.

A. Dutta, O. Ma, M. Toledo, M. Buman, and D. Bliss. ICMLA, page 339-346. IEEE Computer Society, (2016)

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Martin Bumann

Mark Bumann-Melnyk

Axel Bumann

Horst Bumann

Other publications of authors with the same name

A statistical estimation framework for energy expenditure of physical activities from a wrist-worn accelerometer.Q. Wang, S. Lohit, M. Toledo, M. Buman, and P. Turaga. EMBC, page 2631-2635. IEEE, (2016)Comparing Gaussian Mixture Model and Hidden Markov Model to Classify Unique Physical Activities from Accelerometer Sensor Data.A. Dutta, O. Ma, M. Toledo, M. Buman, and D. Bliss. ICMLA, page 339-346. IEEE Computer Society, (2016)PI-Net: A Deep Learning Approach to Extract Topological Persistence Images.A. Som, H. Choi, K. Ramamurthy, M. Buman, and P. Turaga. CVPR Workshops, page 3639-3648. Computer Vision Foundation / IEEE, (2020)Multimodal Time-Series Activity Forecasting for Adaptive Lifestyle Intervention Design.A. Mamun, K. Leonard, M. Buman, and H. Ghasemzadeh. BSN, page 1-4. IEEE, (2022)A Multi-featured Approach for Wearable Sensor-Based Human Activity Recognition.D. Yazdansepas, A. Niazi, J. Gay, F. Maier, L. Ramaswamy, K. Rasheed, and M. Buman. ICHI, page 423-431. IEEE Computer Society, (2016)Using periodicity intensity to detect long term behaviour change.F. Hu, A. Smeaton, E. Newman, and M. Buman. UbiComp/ISWC Adjunct, page 1069-1074. ACM, (2015)Learning approach for classification of GENEActiv accelerometer data for unique activity identification.A. Dutta, O. Ma, M. Buman, and D. Bliss. BSN, page 359-364. IEEE, (2016)Self-Experimentation for Behavior Change: Design and Formative Evaluation of Two Approaches.J. Lee, E. Walker, W. Burleson, M. Kay, M. Buman, and E. Hekler. CHI, page 6837-6849. ACM, (2017)Topological Persistence Guided Knowledge Distillation for Wearable Sensor Data.E. Jeon, H. Choi, A. Shukla, Y. Wang, H. Lee, M. Buman, and P. Turaga. CoRR, (2024)Unsupervised Pre-trained Models from Healthy ADLs Improve Parkinson's Disease Classification of Gait Patterns.A. Som, N. Krishnamurthi, M. Buman, and P. Turaga. EMBC, page 784-788. IEEE, (2020)

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Disambiguation of "Buman, Matthew P."

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URL
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Comparing Gaussian Mixture Model and Hidden Markov Model to Classify Unique Physical Activities from Accelerometer Sensor Data.

Please choose a person to relate this publication to

Martin Bumann

Mark Bumann-Melnyk

Axel Bumann

Axel Bumann

Horst Bumann

Other publications of authors with the same name

Disambiguation

BibSonomy

Disambiguation of "Buman, Matthew P."

copydeleteadd this publication to your clipboardcommunity posthistory of this postURLDOIBibTeXEndNoteAPAChicagoDIN 1505HarvardMSOffice XML Comparing Gaussian Mixture Model and Hidden Markov Model to Classify Unique Physical Activities from Accelerometer Sensor Data.

Please choose a person to relate this publication to

Martin Bumann

Mark Bumann-Melnyk

Axel Bumann

Axel Bumann

Horst Bumann

Other publications of authors with the same name

Disambiguation

copy delete add this publication to your clipboard
community post
history of this post
URL
DOI
BibTeX
EndNote
APA
Chicago
DIN 1505
Harvard
MSOffice XML

Comparing Gaussian Mixture Model and Hidden Markov Model to Classify Unique Physical Activities from Accelerometer Sensor Data.