Deep Learning Analytics Center of Excellence
MACHINE LEARNING Made SMARTER
Our Deep Learning Analytics team has proven experience in creating specialized machine learning algorithms and deploying them to mobile platforms like smartphones, unmanned underwater vehicles, and aircraft at the edge of the battlefield.
We develop deep learning technologies that support smarter forecasting, threat detection, complicated problem solving, and aid in decision-making. These technologies give warfighters on the front lines access to the power of artificial intelligence.
What is Deep Learning?
Deep learning is a form of machine learning (ML) that "can learn" representations from data itself rather than from programmed instructions. Deep learning can learn to represent very complex patterns on vast amounts of data in simple ways that can help humans and other systems do things faster and cheaper.
Deep learning can be used on variety of input data types including audio, video, text, images, radio waves and machine signals to create applications such as natural language processing, audio recognition, computer vision, and target recognition. At scale, these applications can comb through massive amounts of data that would be impossible for a team of humans to process.
In all domains, deep learning technologies can help our customers complete their missions smarter.
Our Deep Learning Analytics team supported DARPA’s TRACE program, which developed advanced radar target recognition algorithms and demonstrated a low-power, real-time radar target recognition system. Military aircraft often have to fly low enough to visually identify the target, which is dangerous for pilots and can result in errors. Our team capitalized on the reduced runtime complexity of new recognition algorithms and increased computational efficiency of new mobile processors to reduce the run-time size, weight and power (SWAP) of radar target-recognition algorithms.
By bringing deep learning technology to the edge, we’re enabling more powerful target recognition algorithms to be put into action on military aircraft.
What Sets Us Apart
Our Deep Learning Analytics team uses a multidisciplinary and systems-level approach to solving mission-critical problems.
We partner with domain experts to help tailor our systems to meet machine requirements. We invest a significant amount of time not only in training state-of-the-art machine learning engines for our customers, but also deploying them on very small size, weight and power-efficient devices, like field programmable gate arrays and mobile devices, and integrating those research prototypes into existing transition candidates for DoD programs of record.
Our Award-Winning Team
Talented people with proven experience and creative problem-solving skills are critical in any field, but especially in machine learning. Our Deep Learning Analytics experts come from multidisciplinary backgrounds and have been recognized as some of the best in the world. Below is just a sample of the awards the team has won.
“Leadership in Computer Science Award, Washington Academy of Sciences, 2019” – Dr. John Kaufhold
“1st Place in America, iNaturalist Fine-Grained Visual Categorization Challenge, 2018 & 2019” – Jeremy Trammell
Need Help With A Tough Problem?
Machine learning and data science is what we do.
If your government organization has labeled data but lacks the machine learning expertise to solve your hard problems, tell us about it. Our experienced team loves creating faster, cheaper, and better solutions that can be customized for your mission.
"Through data science, research, machine learning, predictive analytics and software engineering, our government and commercial customers can better exploit their data—a tremendous value to their missions."
Chris Brady, President of General Dynamics Mission Systems
General Dynamics Mission Systems acquired Deep Learning Analytics (DLA), LLC, on March 7, 2019. The 5-year-old company provides proven capabilities to harness massive data sets and make advances in computing hardware and algorithms to aid in superior prediction, threat detection, decision-making, an…
The iNaturalist 2018 challenge established that Deep Learning Analytics is very competitive and there is no other organization in the United States that demonstrated similar performance on this data.
In 2017, DARPA's Information Innovation Office (I2O) incorporated Deep Learning Analytics' image manifold work into their "A DARPA Perspective on Artificial Intelligence." If missing data gaps on data manifolds are easier to identify in lower dimensional embeddings, it may also inform research on…