Deep learning for media analysis in defense scenarios--an evaluation of an open-source framework for object detection in intelligence-related image sets
Paul, Taylor H.
MetadataShow full item record
The Department of Defense struggles to develop and maintain cutting-edge software through the Defense Acquisition System. The pace of improvements in machine learning algorithms and software suggests the organization will fail to rapidly develop systems incorporating the latest innovations to meet its intelligence-related media analysis needs. In contrast, the trend of industry and academia releasing algorithms and software under permissive licenses bestows defense organizations with an opportunity. These groups can potentially overcome resource shortfalls and long acquisition timelines by implementing machine learning solutions with open-source software.We test this hypothesis by employing an open-source software library to evaluate publicly available deep learning algorithms on three prior defense-related datasets. We then compare performance of deep convolutional neural networks to past methods for detecting AK-47s, ships, and screenshots in images. Applying proven algorithms through the software framework, we test three object detectors that exceed or match classification performance for all three experiments in a third of the development time available to designers of the previous algorithms. We relate these tests to defense scenarios in order to provide a logical argument and empirical measure of the utility of open-source machine learning frameworks to meet the Department of Defense's intelligence-related media analysis needs.
Approved for public release; distribution is unlimited
Showing items related by title, author, creator and subject.
Kelly, Michael A. (Monterey, California. Naval Postgraduate School, 1993-09);The Department of Defense expends billions of dollars on software development and maintenance annually. Many Department of Defense projects fail to be completed, at large monetary cost to the government, due to the inability ...
Garcia, Julian L.; Holloway, Donovan Jr. (Monterey, CA; Naval Postgraduate School, 2018-09);The Department of Defense (DoD) must continue to develop, sustain, and update its software-based capabilities. For the Department of the Navy (DoN), the life cycle costs of software continue to grow; over time, developing ...
Botsakos, Michael T. (Monterey, California. Naval Postgraduate School, 2007-06);The major problem in the Department of Defense's acquisition of software systems is the growing number of cost and schedule overruns that result in failed software acquisitions. Cost and schedule overruns are the consequence ...