Projekter pr. år
Abstract
We explore risk and rejection for music genre recognition (MGR)
within the minimum risk framework of Bayesian classification.
In this way, we attempt to give an MGR system knowledge that
some misclassifications are worse than others,
and that deferring classification to an expert may be a better option
than forcing a label under high uncertainty.
Our experiments show this approach to have some success
with respect to reducing false positives and negatives.
within the minimum risk framework of Bayesian classification.
In this way, we attempt to give an MGR system knowledge that
some misclassifications are worse than others,
and that deferring classification to an expert may be a better option
than forcing a label under high uncertainty.
Our experiments show this approach to have some success
with respect to reducing false positives and negatives.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | International Conference on Multimedia and Expo |
| Status | Udgivet - 2013 |
| Begivenhed | 2013 IEEE International Conference on Multimedia & Expo - San Jose, USA Varighed: 15 jul. 2013 → 19 jul. 2013 |
Konference
| Konference | 2013 IEEE International Conference on Multimedia & Expo |
|---|---|
| Land/Område | USA |
| By | San Jose |
| Periode | 15/07/2013 → 19/07/2013 |
Fingeraftryk
Dyk ned i forskningsemnerne om 'Music genre recognition with risk and rejection'. Sammen danner de et unikt fingeraftryk.-
Greedy Sparse Approximation and the Automatic Description of Audio and Music Data
Sturm, B. L.
Technology and Production Independent Postdoc Center for Independent Research
01/01/2012 → …
Projekter: Projekt › Forskning
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CoSound
Christensen, M. G., Tan, Z., Jensen, S. H. & Sturm, B. L.
01/01/2012 → 31/12/2015
Projekter: Projekt › Forskning