SBIR/STTR Research Award

TOFENet – Topographic Features Extraction Network

Award identifier a303e5fcda6cde22e2793f23ef17a3fc2f44c84fc2bd7cb569c9b38fbe9b11caAwarding agency Department of Defense · National Geospatial-Intelligence Agency

Award amount

$1,000,000

Program and phase

SBIR · Phase II

Award year

2019

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Award details

Awarding agency
Department of Defense
Branch
National Geospatial-Intelligence Agency
Recipient company
Intelligent Automation, Inc.
Proposal award date
2019-09-26
Contract end date
2020-09-29
UEI
C3QJD7VXG167
Solicitation number
18.1
Topic code
NGA181-001

Research abstract

Topographic features found in ground-based natural images contain information that is useful for a variety of applications including geolocation estimation and navigation. Traditionally, these features have been manually labeled by analysts which is costly and time consuming, especially considering the volume of readily available data. During Phase I, we have demonstrated a novel TOFENet framework for extracting topographic features from still images using a state-of-the-art deep learning based techniques. In this Phase II, we propose to extend the capability to video data, improve robustness to handle variations in lighting, weather and environment, and reduce false positives. IAI will build and deliver a TOFENet software ready for integration, by the end of Phase II.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

1,182 SBIR/STTR records share this UEI (1987–2021). Reported award amounts total $369,972,257. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Defense, National Aeronautics and Space Administration, Department of Transportation, Department of Health and Human Services, National Science Foundation, Department of Homeland Security

Agency intelligence

Department of Defense

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