Object Detection by Simple Fuzzy Classifiers Generated by Boosting

被引：0

作者：

Gabryel, Marcin ^{[1
]}

Korytkowski, Marcin ^{[1
]}

Scherer, Rafal ^{[1
]}

Rutkowski, Leszek ^{[1
]}

机构：

[1] Czestochowa Tech Univ, Inst Computat Intelligence, PL-42200 Czestochowa, Poland

来源：

ARTIFICIAL INTELLIGENCE AND SOFT COMPUTING, PT I | 2013年 / 7894卷

关键词：

PATTERN-RECOGNITION; RETRIEVAL;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Finding key points based on SURF and SIFT and size of their vector reduction is a classical approach for object recognition systems. In this paper we present a new framework for object recognition based on generating simple fuzzy classifiers using key points and boosting meta learning to distinguish between one known class and other classes. We tested proposed approach on a known image dataset.

引用

页码：540 / 547

页数：8

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