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NSWC Crane engineer leverages resources to conduct deep learning research

By NSWC Crane Corporate Communications | July 2, 2019

CRANE, Ind. – A Naval Surface Warfare Center, Crane Division (NSWC Crane) employee recently completed artificial intelligence research to enhance Electronic Warfare (EW) capabilities. David Emerson, an engineer at NSWC Crane, recently defended his research that uses deep learning to process images and determine distances between objects in a scene.

Self-driving cars are an example of a system that uses deep learning to reconstruct scenes in 3-D, but Emerson explains there is interference that influences the effectiveness of currently used methodology. Emerson says depth estimation is one of the most challenging problems in computer vision.

“The human eye can see and understand depth in a scene,” says Emerson. “A computer sees 2-D images and has to calculate the distance to reach an ‘understanding’ of depth between objects. In my Depth from Defocus method, I took one photo in-focus and one photo out-of-focus and constructed a 3-D image.”

Emerson’s Depth from Defocus (DfD) using deep learning (DL) methodology out-performed previously used methods, significantly increased the speed of the process, and was more robust in its ability to handle images in low-lighting conditions.

“In the military, technology is used to determine long distances in the field,” says Emerson. “DfD and deep learning methodology has potential future applications that could considerably improve the warfighter’s speed and capability, all while remaining stealthy.”

Emerson built his research from his many years of Electronic Warfare (EW) expertise at NSWC Crane. He received his Master’s Degree in Computer Engineering from Indiana University--Purdue University Indianapolis (IUPUI). Then, IUPUI established an Electrical and Computer Engineering (ECE) doctoral program, and Emerson will be the first-ever PhD to graduate this summer. Emerson’s research was partially funded first with a Department of Defense (DoD) Science, Mathematics And Research for Transformation (SMART) Scholarship for Service Program, and then followed with full sponsorship by the NSWC Crane Ph.D. Fellowship Program.

“I would not have been able to pursue this research if it weren’t for the flexibility and support of my manager, Christopher Crombar, and team,” says Emerson. “Overall, the learning process has been beneficial. Machine Learning and Deep Learning are not going to go away; researching the latest trends now can translate to solving future problems for military, industry, and academia. I am excited to apply everything I’ve learned over the past few years to help people and save lives.”

NSWC Crane is a naval laboratory and a field activity of Naval Sea Systems Command (NAVSEA) with mission areas in Expeditionary Warfare, Strategic Missions and Electronic Warfare. The warfare center is responsible for multi-domain, multi- spectral, full life cycle support of technologies and systems enhancing capability to today's Warfighter.