Robust Recognition via Information Theoretic Learning (SpringerBriefs in Computer Science)
6 Angebote vergleichen
| Preise | 2014 | 2015 | 2022 |
|---|---|---|---|
| Schnitt | Fr. 48.53 (€ 49.58)¹ | Fr. 52.28 (€ 53.42)¹ | Fr. 20.99 (€ 21.45)¹ |
| Nachfrage |
1
Symbolbild
Robust Recognition via Information Theoretic Learning (2014)
DE PB NWISBN: 9783319074153 bzw. 3319074156, in Deutsch, Springer-Verlag Gmbh Okt 2014, Taschenbuch, neu.
Von Händler/Antiquariat, Agrios-Buch [57449362], Bergisch Gladbach, NRW, Germany.
Neuware - This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy. The authors resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency, the brief introduces the additive and multiplicative forms of half-quadratic optimization to efficiently minimize entropy problems and a two-stage sparse presentation framework for large scale recognition problems. It also describes the strengths and deficiencies of different robust measures in solving robust recognition problems. 110 pp. Englisch.
Neuware - This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy. The authors resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency, the brief introduces the additive and multiplicative forms of half-quadratic optimization to efficiently minimize entropy problems and a two-stage sparse presentation framework for large scale recognition problems. It also describes the strengths and deficiencies of different robust measures in solving robust recognition problems. 110 pp. Englisch.
2
Symbolbild
Robust Recognition via Information Theoretic Learning (2014)
DE PB NWISBN: 9783319074153 bzw. 3319074156, in Deutsch, Springer-Verlag Gmbh Okt 2014, Taschenbuch, neu.
Von Händler/Antiquariat, Rheinberg-Buch [53870650], Bergisch Gladbach, NRW, Germany.
Neuware - This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy. The authors resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency, the brief introduces the additive and multiplicative forms of half-quadratic optimization to efficiently minimize entropy problems and a two-stage sparse presentation framework for large scale recognition problems. It also describes the strengths and deficiencies of different robust measures in solving robust recognition problems. 110 pp. Englisch.
Neuware - This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy. The authors resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency, the brief introduces the additive and multiplicative forms of half-quadratic optimization to efficiently minimize entropy problems and a two-stage sparse presentation framework for large scale recognition problems. It also describes the strengths and deficiencies of different robust measures in solving robust recognition problems. 110 pp. Englisch.
3
Symbolbild
Robust Recognition via Information Theoretic Learning (2014)
DE PB NWISBN: 9783319074153 bzw. 3319074156, in Deutsch, Springer-Verlag Gmbh Okt 2014, Taschenbuch, neu.
Lieferung aus: Deutschland, Versandkostenfrei.
Von Händler/Antiquariat, Rhein-Team Lörrach Ivano Narducci e.K. [57451429], Lörrach, Germany.
Neuware - This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy. The authors resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency, the brief introduces the additive and multiplicative forms of half-quadratic optimization to efficiently minimize entropy problems and a two-stage sparse presentation framework for large scale recognition problems. It also describes the strengths and deficiencies of different robust measures in solving robust recognition problems. 110 pp. Englisch.
Von Händler/Antiquariat, Rhein-Team Lörrach Ivano Narducci e.K. [57451429], Lörrach, Germany.
Neuware - This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy. The authors resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency, the brief introduces the additive and multiplicative forms of half-quadratic optimization to efficiently minimize entropy problems and a two-stage sparse presentation framework for large scale recognition problems. It also describes the strengths and deficiencies of different robust measures in solving robust recognition problems. 110 pp. Englisch.
4
Symbolbild
Robust Recognition via Information Theoretic Learning
DE PB NWISBN: 9783319074153 bzw. 3319074156, in Deutsch, Springer International Publishing AG, Taschenbuch, neu.
Von Händler/Antiquariat, THE SAINT BOOKSTORE [51194787], Southport, United Kingdom.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
6
Robust Recognition via Information Theoretic Learning
~EN NWISBN: 9783319074153 bzw. 3319074156, vermutlich in Englisch, neu.
Lieferung aus: Deutschland, 1-2 Werktage.
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Die Beschreibung dieses Angebotes ist von geringer Qualität oder in einer Fremdsprache. Trotzdem anzeigen
Lade…