Computationally efficient SVM multi-class image recognition with confidence measures (Articolo in rivista)

Type

• Prodotto della ricerca (Classe)
• Articolo in rivista (Classe)

Label

• Computationally efficient SVM multi-class image recognition with confidence measures (Articolo in rivista) (literal)

Anno

• 2011-01-01T00:00:00+01:00 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi

• 10.1016/j.fusengdes.2011.02.081 (literal)

Alternative label

• Lázaro Makili; Jesús Vega; Sebastián Dormido-Canto; Ignacio Pastor; Andrea Murari (2011)
  Computationally efficient SVM multi-class image recognition with confidence measures
  in Fusion engineering and design; ELSEVIER SCIENCE SA, PO BOX 564, 1001 LAUSANNE (Svizzera)
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Lázaro Makili; Jesús Vega; Sebastián Dormido-Canto; Ignacio Pastor; Andrea Murari (literal)

Pagina inizio

• 1213 (literal)

Pagina fine

• 1216 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#altreInformazioni

• La rivista è pubblicata anche online con ISSN 1873-7196 (Editore: Elsevier Science SA) (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url

• http://www.sciencedirect.com/science/article/pii/S0920379611002511 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume

• 86 (literal)

Rivista

• Fusion engineering and design (Rivista)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note

• Issues 6-8, ottobre (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali

• 4 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroFascicolo

• 6-8 (literal)

Note

• Scopu (literal)
• ISI Web of Science (WOS) (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• a Dpto. Informática y Automática - UNED, Madrid, Spain; b Asociación EURATOM/CIEMAT para Fusión, Madrid, Spain; c Associazione EURATOM-CIEMAT per la Fusione, Consorzio RFX, Padova, Italy. (Lázaro Makili a, Jesús Vega b, Sebastián Dormido-Canto a, Ignacio Pastor b, Andrea Murari c) (literal)

Titolo

• Computationally efficient SVM multi-class image recognition with confidence measures (literal)

Abstract

• Typically, machine learning methods produce non-qualified estimates, i.e. the accuracy and reliability of the predictions are not provided. Transductive predictors are very recent classifiers able to provide, simultaneously with the prediction, a couple of values (confidence and credibility) to reflect the quality of the prediction. Usually, a drawback of the transductive techniques for huge datasets and large dimensionality is the high computational time. To overcome this issue, a more efficient classifier has been used in a multi-class image classification problem in the TJ-II stellarator database. It is based on the creation of a hash function to generate several \"one versus the rest\" classifiers for every class. By using Support Vector Machines as the underlying classifier, a comparison between the pure transductive approach and the new method has been performed. In both cases, the success rates are high and the computation time with the new method is up to 0.4 times the old one. (literal)

Editore

• ELSEVIER SCIENCE SA (Editore)

Prodotto di

• Esperimento RFX ed attività collegate (ET.P05.003.001) (Modulo)
• Institute of ionized gas (IGI) (Istituto)

Autore CNR

• ANDREA MURARI (Unità di personale interno)

Insieme di parole chiave

• Keywords of "Computationally efficient SVM multi-class image recognition with confidence measures" (Insieme di parole chiave)

Incoming links:

Prodotto

• Institute of ionized gas (IGI) (Istituto)
• Esperimento RFX ed attività collegate (ET.P05.003.001) (Modulo)

Autore CNR di

• ANDREA MURARI (Unità di personale interno)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#rivistaDi

• Fusion engineering and design (Rivista)

Editore di

• ELSEVIER SCIENCE SA (Editore)

Insieme di parole chiave di

• Keywords of "Computationally efficient SVM multi-class image recognition with confidence measures" (Insieme di parole chiave)