Machine Learning for the Detection of Oil Spills in Satellite Radar Images View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

1998-02

AUTHORS

Miroslav Kubat, Robert C. Holte, Stan Matwin

ABSTRACT

During a project examining the use of machine learning techniques for oil spill detection, we encountered several essential questions that we believe deserve the attention of the research community. We use our particular case study to illustrate such issues as problem formulation, selection of evaluation measures, and data preparation. We relate these issues to properties of the oil spill application, such as its imbalanced class distribution, that are shown to be common to many applications. Our solutions to these issues are implemented in the Canadian Environmental Hazards Detection System (CEHDS), which is about to undergo field testing. More... »

PAGES

195-215

Journal

TITLE

Machine Learning

ISSUE

2-3

VOLUME

30

Author Affiliations

Identifiers

URI

http://scigraph.springernature.com/pub.10.1023/a:1007452223027

DOI

http://dx.doi.org/10.1023/a:1007452223027

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1025850532


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