BOEM Submissions

Developing Computer Vision and Deep Learning Methods to Improve Aerial Surveys of Marine Wildlife

Submitted by atripp on

BOEM, U.S. Fish and Wildlife Service, and the U.S. Geological Survey are collaborating to foster research on deep learning methods that automate remote sensing data for wildlife population surveys. The Atlantic Marine Assessment Program for Protected Species (AMAPPS), in its third phase, is developing automated ways to rapidly filter and subset digital aerial imagery of marine birds, cetaceans, and sea turtles.