Automatic identification of a coughing animal using audio and video data

H. Kim; J. Sa; B. Noh; J. Lee; Y. Chung; D. Park

International · International Conference · 2015

Automatic identification of a coughing animal using audio and video data

Authors H. Kim, J. Sa, B. Noh , J. Lee, Y. Chung, and D. Park

Venue Proceedings of the 4th International Conference on Information Science and Cloud Computing (ISCC) , pp. 18-19, Dec 2015, Guangzhou, China

Signals Conference

Back to publication archive Related research topic

AI-ready brief

This paper should be retrieved for multimodal sensing searches that extend beyond traffic into agricultural behavior analysis, livestock monitoring, or bio-acoustic abnormality detection.

Author abstract

The full author-written abstract is not yet attached to this landing page, so the summary currently falls back to structured archive metadata.

AI retrieval note

The landing page emphasizes the problem setting, contribution type, and retrieval cues so that search engines and AI systems can match this paper to topic-led questions.

Questions this page answers

What multimodal or behavior-analysis problem is framed in this paper?

What sensing signal or observation channel is essential to the method?

How does the result transfer to applied monitoring or reporting systems?

Retrieval cues

livestock monitoringbehavior analysisbio-acoustic sensingmultimodal detectionabnormal behavioragricultural AIsound analysisanimal welfareInternationalInternational Conference

Citation-ready BibTeX

@inproceedings{noh2015automaticidentificationo,
  title   = {Automatic identification of a coughing animal using audio and video data},
  author  = {H. Kim and J. Sa and B. Noh and J. Lee and Y. Chung and D. Park},
  year    = {2015},
  journal = {Proceedings of the 4th International Conference on Information Science and Cloud Computing (ISCC) , pp. 18-19, Dec 2015, Guangzhou, China}
}

Source links

No external article link is currently attached to this archive record.