The eleven ‘best’ candidate OBIA algorithms used in this study to identify beluga whale locations.

The eleven ‘best’ candidate OBIA algorithms used in this study to identify beluga whale locations.

<p>The segment algorithm was EDGE and the merge algorithm was FAST LAMBDA for all of the eleven algorithms listed.</p>

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Bibliographic Details
Main Author:	John Iacozza (5787789) (author)
Other Authors:	Bryanna Sherbo (17714231) (author), Cortney Watt (20189736) (author)
Published:	2024
Subjects:	Biochemistry Space Science Biological Sciences not elsewhere classified Information Systems not elsewhere classified texture variance attributes delphinapterus leucas )</ based image analysis false positive rate false negative rate automated count deviation sized beluga whales enumerate beluga whales used spectral mean traditional detection methods processing large amounts free panchromatic image div >< p 3 satellite imagery algorithm detected imagery satellite imagery false positives automated results whales detected test imagery viable solution various algorithms significant advantages reliably identify reading training open water one another ocean conditions manually review limiting factor human read experienced readers determining counts detection time best algorithm autodetection algorithm algorithm could
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Summary:	<p>The segment algorithm was EDGE and the merge algorithm was FAST LAMBDA for all of the eleven algorithms listed.</p>

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