Comparing the Accuracy of Multi-Source Data Integration for Two Supervised Image Classification Methods: Maximum Likelihood and Artificial Neural Network

Hillary Tribby; Daniel Unger

Comparing the Accuracy of Multi-Source Data Integration for Two Supervised Image Classification Methods: Maximum Likelihood and Artificial Neural Network

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Research output: Other contribution

Original language	Undefined/Unknown
State	Published - Jan 1 2006

Publication series

Name	Faculty Presentations

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Comparing the Accuracy of Multi-Source Data Integration for Two S

http://scholarworks.sfasu.edu/spatialsci_facultypres/24

Cite this

@misc{09da991e65784790849d934948a93762,

title = "Comparing the Accuracy of Multi-Source Data Integration for Two Supervised Image Classification Methods: Maximum Likelihood and Artificial Neural Network",

author = "Hillary Tribby and Daniel Unger",

year = "2006",

month = jan,

day = "1",

language = "Undefined/Unknown",

series = "Faculty Presentations",

type = "Other",

}