Activity Recognition from Daily-Life Sounds Using Unsupervised Learning with Dirichlet Multinomial Mixture Models.

Sadohara K, Miyata N

DOI: 10.3390/s26051509
Published: 2026 Feb 27
Container: Sensors (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/s26051509,
  title = {Activity Recognition from Daily-Life Sounds Using Unsupervised Learning with Dirichlet Multinomial Mixture Models.},
  author = {Sadohara K and Miyata N},
  year = {2026},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s26051509},
  url = {https://doi.org/10.3390/s26051509}
}

RIS

TY  - JOUR
TI  - Activity Recognition from Daily-Life Sounds Using Unsupervised Learning with Dirichlet Multinomial Mixture Models.
AU  - Sadohara K
AU  - Miyata N
PY  - 2026
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s26051509
UR  - https://doi.org/10.3390/s26051509
ER  -

APA

K, S., & N, M. (2026). Activity Recognition from Daily-Life Sounds Using Unsupervised Learning with Dirichlet Multinomial Mixture Models.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s26051509

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pubmed · retrieved 2026-09-25T20:18:05.932Z