Daniel Brown was nominated by his co-worker, Chris Capraro, for his “innovative developments in machine learning and neuromorphic computing,” per a MACNY news release. SRC is a nonprofit corporation headquartered in Cicero that focuses on areas that include defense, environment, and intelligence. “From all of us at MACNY, I would like to congratulate Dan and […]
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Daniel Brown was nominated by his co-worker, Chris Capraro, for his “innovative developments in machine learning and neuromorphic computing,” per a MACNY news release.
SRC is a nonprofit corporation headquartered in Cicero that focuses on areas that include defense, environment, and intelligence.
“From all of us at MACNY, I would like to congratulate Dan and SRC on their innovative accomplishments and receiving this well-deserved honor,” Randy Wolken, president & CEO of MACNY, said in the March 6 announcement. “Again this year, we received nominations for many well-qualified candidates who are considered outstanding innovators by their peers and colleagues. The committee was thoroughly impressed by Dan’s commitment to innovation and the continued progress and success he has brought to SRC, Inc. On behalf of the MACNY membership, we look forward to recognizing Dan and SRC for their many innovative achievements at MACNY’s 107th annual dinner.”
As part of MACNY’s tradition, the organization will honor Brown at its 107th annual dinner, which will include his SRC colleagues and an audience of more than 600 members of the manufacturing and business community from Central and Upstate New York.
The dinner is set for May 21 at the SRC Arena and Events Center on the campus of Onondaga Community College in the town of Onondaga.
About Brown’s work
Brown recently helped transition “state-of-the-art” machine-learning methods for detecting very small moving objects in infrared camera imagery for testing with SRC’s counter-UAS (C-UAS) technology.
This is a “tedious” task for an operator, which is “error prone and fatiguing.” Brown’s contributions have already shown “significant promise” at several C-UAS exercises and may soon help military members in the field.
UAS, or unmanned aircraft system, includes a drone and equipment used to control its flight. A drone is also referred to in the industry as an unmanned aerial vehicle, or UAV.
Brown was also able to configure and develop software for a very low-size, weight and power (SWaP) computational system on a chip from Santa Clara, California–based Nvidia Corp. (NASDAQ: NVDA) called a TX2. This computer hardware uses about 10-15 watts of power, is less than 7 inches square and 2 inches thick, and weighs about 3.5 pounds.
Brown was able to decode the full video stream, perform machine learning for moving object detection, augment the video with target bounding boxes, and re-encode the video stream in real-time. His effort is described as a “huge accomplishment” and allows SRC to add “critical, state-of-the-art machine learning” to its existing C-UAS systems with minimal impact on SWaP.
Brown also recently developed, “for the first time ever,” parallel-processing techniques for the neuromorphic True North system. At first, just a couple processors, then 16 and 32 - all working “simultaneously.” He processed synthetic aperture radar (SAR) imagery/targets, tanks and trucks using the moving and stationary target acquisition and recognition (MSTAR) data for automatic target recognition, which he has briefed to military generals, federal lawmakers, and others.
“Dan’s efforts have enabled innovation at SRC and led the way in a variety of ways. Dan has focused his technical work on developing advanced hardware and software technologies that continually contribute to the main and critical objectives of our bio-inspired and machine learning efforts,” Capraro said in the nomination form.