Publicacions CVC -- Edit Record

	Publicacions CVC Home \| Show All \| Simple Search \| Advanced Search \| Add Record \| Import	You must login to submit this form! Login Quick Search: Field: contains: ...
	Edit the following record:

Author	...				is Editor
Title	...			Type
Year	...	Publication	...	Abbreviated Journal	...
Volume	...	Issue	...	Pages	...
Keywords	...
Abstract	Intravascular ultrasound (IVUS) represents a powerful imaging technique to explore coronary vessels and to study their morphology and histologic properties. In this paper, we characterize different tissues based on radial frequency, texture-based, and combined features. To deal with the classification of multiple tissues, we require the use of robust multi-class learning techniques. In this sense, error-correcting output codes (ECOC) show to robustly combine binary classifiers to solve multi-class problems. In this context, we propose a strategy to model multi-class classification tasks using sub-classes information in the ECOC framework. The new strategy splits the classes into different sub-sets according to the applied base classifier. Complex IVUS data sets containing overlapping data are learnt by splitting the original set of classes into sub-classes, and embedding the binary problems in a problem-dependent ECOC design. The method automatically characterizes different tissues, showing performance improvements over the state-of-the-art ECOC techniques for different base classifiers. Furthermore, the combination of RF and texture-based features also shows improvements over the state-of-the-art approaches.
Address	...
Corporate Author	...			Thesis
Publisher	...	Place of Publication	...	Editor	...
Language	...	Summary Language	...	Original Title	...
Series Editor	...	Series Title	...	Abbreviated Series Title	...
Series Volume	...	Series Issue	...	Edition	...
ISSN	...	ISBN	...	Medium	...
Area	...	Expedition	...	Conference	...
Notes	...			Approved	yes no
Location
Call Number	...			Serial
Marked	yes no	Copy		Selected	yes no
User Keys	...
User Notes	...			User File	...
User Groups	...			Cite Key	...
Related	...
File
URL	...			DOI	...
	Online publication. Cite with this text: ...

Location Field:	my name & email address

Home

SQL Search | Library Search | Show Record | Extract Citations

Help