Applications of generalized learning in image recognition

Author

Min, Yao ; Zhiwei, Jiang ; Wensheng, Yi ; Xiaoming, Zhao

Author_Institution

Coll. of Comput. Sci. & Technol., Zhejiang Univ., Hangzhou, China

fYear

2005

fDate

26-28 May 2005

Firstpage

159

Lastpage

162

Abstract

Generalized learning model, GLM for short, is a new kind of machine learning model which fuses symbolic learning, connective learning, fuzzy learning, evolutionary learning and statistical learning together. By introducing generalized learning into image recognition, this paper presents a new kind of image recognition model, GLIRM for short. The distinguished advantage of GLIRM is its adaptive learning ability. Through practical application in remote sensing image recognition, satisfactory results have been achieved.

Keywords

image recognition; learning (artificial intelligence); learning systems; remote sensing; GLIRM; adaptive learning; connective learning; evolutionary learning; fuzzy learning; generalized learning; image processing; image recognition; machine learning; pattern recognition; remote sensing; statistical learning; symbolic learning; Application software; Artificial neural networks; Brain modeling; Computer science; Educational institutions; Fuses; Image recognition; Learning systems; Machine learning; Statistical learning;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Interface and Control, 2005. Proceedings. 2005 First International Conference on

Print_ISBN

0-7803-8902-6

Type

conf

DOI

10.1109/ICNIC.2005.1499867

Filename

1499867