Machine learning for the detection of oil spills in satellite radar images

被引：808

作者：

Kubat, M ^{[1
]}

Holte, RC ^{[1
]}

Matwin, S ^{[1
]}

机构：

[1] Univ Ottawa, Sch Informat Technol & Engn, Ottawa, ON K1N 6N5, Canada

来源：

MACHINE LEARNING | 1998年 / 30卷 / 2-3期

关键词：

inductive learning; classification; radar images; methodology;

D O I：

10.1023/A:1007452223027

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页码：195 / 215

页数：21