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“ THE TWO YEARS THAT I WAS ABLE TO SPEND WITH A NON-STOP FOCUS ON MACHINE LEARNING AND AI HAVE MEANT I ’ VE BEEN ABLE TO BRING BACK A LOT OF BENEFITS ”
— TSgt . Armando Cabrera , US Air Force
you don ’ t need experience as an image analyst , to understand what the images show . SAR sensors can penetrate things like weather or smoke , but the drawback is it ’ s hard to interpret the image itself . I ’ m hoping that with this capability that we ’ re creating , it can be used during events that usually don ’ t deploy it for . We can automatically use the sensor to penetrate through smoke or clouds and easily get additional information that we normally wouldn ’ t have .”
The project uses learning algorithms trained on paired SAR and more easily understood electro-optical ( EO ) images . “ It ’ s able to learn what a SAR image will look like compared with an EO image , and over time it will pick up the characteristics of the SAR image that are equivalent to EO image . That
DECEMBER 2020