Image classification with structured self-organization map

Z. Wang, M. Hagenbuchner, A. C. Tsoi, S. Y. Cho, Zheru Chi

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

14 Citations (Scopus)

Abstract

Adaptive processing of structured data using supervised learning scheme has been successfully applied to many domains, e.g., molecular biology, image classification and retrieval. A self organizing map (SOM) type algorithm for processing of structured data using an unsupervised learning approach has recently been proposed. In this paper, we present an approach using quadtree representation to extract an image structure, and the application of such structured SOM to image classification problems. Encouraging results achieved by using only six simple visual features show that the structured SOM works well for structural information.
Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
Pages1918-1923
Number of pages6
Publication statusPublished - 1 Jan 2002
Event2002 International Joint Conference on Neural Networks (IJCNN '02) - Honolulu, HI, United States
Duration: 12 May 200217 May 2002

Conference

Conference2002 International Joint Conference on Neural Networks (IJCNN '02)
CountryUnited States
CityHonolulu, HI
Period12/05/0217/05/02

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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