Identificador persistente para citar o vincular este elemento:
http://hdl.handle.net/10553/16113
| Título: | Exploring the use of local descriptors for fish recognition in LifeCLEF 2015 | Autores/as: | Cabrera-Gámez, Jorge Castrillón-Santana, Modesto Domínguez-Brito, Antonio Hernández Sosa, José Daniel Isern-González, Josep Lorenzo-Navarro, Javier |
Clasificación UNESCO: | 120304 Inteligencia artificial 120325 Diseño de sistemas sensores |
Fecha de publicación: | 2015 | Publicación seriada: | CEUR Workshop Proceedings | Conferencia: | 16th Conference and Labs of the Evaluation Forum, CLEF 2015 | Resumen: | This paper summarizes the proposal made by the SIANI team for the LifeCLEF 2015 Fish task. The approach makes use of standard detection techniques, applying a multiclass SVM based classifier on large enough Regions Of Interest (ROIs) automatically extracted from the provided video frames. The selection of the detection and classification modules is based on the best performance achieved for the validation dataset consisting of 20 annotated videos. For that dataset, the best classification achieved for an ideal detection module, reaches an accuracy around 40%. | URI: | http://hdl.handle.net/10553/16113 | ISSN: | 1613-0073 | Fuente: | CEUR Workshop Proceedings[ISSN 1613-0073],v. 1391 |
| Colección: | Actas de congresos |
Artículo
Adobe PDF (406,18 kB)
Este elemento está sujeto a una licencia Licencia Creative Commons
