In-Q-Tel, a U.S. government-funded venture capital firm, and AI.Reverie, a startup based in New York that creates synthetic data to train machine learning algorithms, have released a dataset of satellite imagery. The duo released the dataset, which combines 250 real satellite images and more than 50,000 synthetic images, to advance the development of computer vision systems that can detect aircraft. The images contain numerous labels, such as an aircraft’s length, wingspan, and number of engines.
Identifying Aircraft in Satellite Imagery
Michael McLaughlin is a research analyst at the Center for Data Innovation. He researches and writes about a variety of issues related to information technology and Internet policy, including digital platforms, e-government, and artificial intelligence. Michael graduated from Wake Forest University, where he majored in Communication with Minors in Politics and International Affairs and Journalism. He received his Master’s in Communication at Stanford University, specializing in Data Journalism.
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