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BYU's smart object recognition algorithm doesn't need humans
Date:1/16/2014

s scored in the 95-98% range.

The team has also tested their algorithm on a dataset of fish images from BYU's biology department that included photos of four species: Yellowstone cutthroat, cottid, speckled dace and whitefish. The algorithm was able to distinguish between the species with 99.4% accuracy.

Lee said the results show the algorithm could be used for a number of applications, from detecting invasive fish species (think of the carp in Utah Lake) to identifying flaws in produce such as apples on a production line.

"It's very comparable to other object recognition algorithms for accuracy, but, we don't need humans to be involved," Lee said. "You don't have to reinvent the wheel each time. You just run it."


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Contact: Todd Hollingshead
toddh@byu.edu
801-422-8373
Brigham Young University
Source:Eurekalert  

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