YYC: A fast performance incremental algorithm for finding typical testors

Eduardo Alba-Cabrera, Julio Ibarra-Fiallo, Salvador Godoy-Calderon, Fernando Cervantes-Alonso

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

8 Citas (Scopus)

Resumen

The last few years have seen an important increase in research publications dealing with external typical testor-finding algorithms, while internal ones have been almost forgotten or modified to behave as external on the basis of their alleged poor performance. In this research we present a new internal typical testor-finding algorithm called YYC that incrementally calculates typical testors for the currently analized set of basic matrix rows by searching for compatible sets. The experimentally measured performance of this algorithm stands out favorably in problems where other external algorithms show very low performance. Also, a comparative analysis of its efficiency is done against some external typical testor-finding algorithms published during the last few years.

Idioma originalInglés
Título de la publicación alojadaProgress in Pattern Recognition Image Analysis, Computer Vision and Applications - 19th Iberoamerican Congress, CIARP 2014, Proceedings
EditoresEduardo Bayro-Corrochano, Edwin Hancock
EditorialSpringer Verlag
Páginas416-423
Número de páginas8
ISBN (versión digital)9783319125671
DOI
EstadoPublicada - 2014
Evento19th Iberoamerican Congress on Pattern Recognition, CIARP 2014 - Puerto Vallarta, México
Duración: 2 nov. 20145 nov. 2014

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen8827
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia19th Iberoamerican Congress on Pattern Recognition, CIARP 2014
País/TerritorioMéxico
CiudadPuerto Vallarta
Período2/11/145/11/14

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