Incremental learning in autonomous systems: Evolving cnnectionist systems for on-line image and speech recognition

被引：0
|
作者：
Kasabov, N [1 ]
Zhang, D [1 ]
Pang, PS [1 ]
机构：
[1] Auckland Univ Technol, Knowledge Engn & Discovery Res Inst, Auckland, New Zealand
来源：
2005 IEEE WORKSHOP ON ADVANCED ROBOTICS AND ITS SOCIAL IMPACTS | 2005年
关键词：
autonomous systems; incremental learning; adaptive systems; multimodal systems; image recognition; speech recognition; evolving connectionist systems (ECOS); evolving growing cluster classifier (EGCC); online adaptation;
D O I：
暂无
中图分类号：
TP3 [计算技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper presents an integrated approach to incremental learning in autonomous systems, that includes both pattern recognition and feature selection. The approach utilizes evolving connectionist systems (ECoS) and is applied on on-line image and speech pattern learning and recognition tasks.. The experiments show that ECoS are a suitable paradigm for building autonomous systems for learning and navigation in a new environment using both image and speech modalities.
引用
收藏
页码：120 / 125
页数：6
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