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Communication Dans Un Congrès Année : 2008

Weakly supervised learning using proportion-based information : an application to fisheries acoustics

Résumé

This paper addresses the inference of probabilistic classification models using weakly supervised learning. In contrast to previous work, the use of proportion-based training data is investigated in combination to non-linear classification models. An application to fisheries acoustics and fish school classification is considered and experiments are reported for synthetic and real datasets.
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Dates et versions

hal-01250428 , version 1 (04-01-2016)

Identifiants

Citer

Ronan Fablet, Riwal Lefort, C. Scalarin, Jean-Marc Boucher, Jacques Masse. Weakly supervised learning using proportion-based information : an application to fisheries acoustics. ICPR 2008 : 19th international conference on Pattern Recognition, Dec 2008, Tampa, United States. pp.1 - 4, ⟨10.1109/ICPR.2008.4761065⟩. ⟨hal-01250428⟩
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