Active learning for detecting a spectrally variable subject in color infrared imagery

Patricia G. Foschi, Huan Liu

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations

Abstract

To classify Egeria densa, Brazilian waterweed, in scan-digitized color infrared aerial photographs, we are developing an interactive computer system based on data-mining techniques with active learning capabilities. Key components of the system are: feature extraction, automatic classification, active learning, and experimental evaluation.

Original languageEnglish (US)
Pages (from-to)1509-1517
Number of pages9
JournalPattern Recognition Letters
Volume25
Issue number13
DOIs
StatePublished - Oct 1 2004
EventPattern Recognition for Remote Sensing - Niagra Falls, Canada
Duration: Aug 1 2002Aug 1 2002

Keywords

  • Active learning
  • CIR imagery
  • Data mining
  • Feature extraction

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Artificial Intelligence

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