SBIR/STTR Research Award
Threat Detection Using Artificial Intelligence and Machine Learning
Award amount
$149,992Program and phase
SBIR · Phase IAward year
2018Award details
- Awarding agency
- Department of Defense
- Branch
- Air Force
- Recipient company
- ETEGENT TECHNOLOGIES, LTD.
- Proposal award date
- 2018-01-17
- Contract end date
- 2018-10-17
- UEI
- FLKAMJTNTDY1
- Solicitation number
- 2017.2
- Topic code
- AF172-010
Research abstract
In both the commercial and military environments, the data explosion has both facilitated and required the development of automatic exploitation algorithms. In this phase I effort we will apply current state of the art DCNNs to characterize and detect threats at forward operating bases(FOB).Our solution is based on the ImageNet classes, which will be modified and adapted by the analyst via transfer learning to characterize regions of interest within the mosaic of sensor imagery.This information will be presented to the analyst via our NTellus heatmap tool. Labels and interactions specific to FOB activities will be gathered to define a normalcy model.
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.
- Validation and Evaluation with Incomplete Labels (VEIL)
- CAPTURE - Context Aware Preprocessing Technology for Ultra -Wide Band RF Exploitation
- Single-View Polarimetric Long-Range Maritime Target Shape Recovery
- Easy to Use Tool to Estimate Turbine Engine Performance and Mission Capability for Rotorcraft
- Exploitation of Ephemeral Features in Sonar Classification Algorithms
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- Discovery of Anomalous Activity in Real Time (DAART)
- NVision: Leveraging Artificial Intelligence and Machine Learning to Detect Threats
- Threat Detection Using Artificial Intelligence and Machine Learning
- Threat Detection Using Artificial Intelligence and Machine Learning
- MATILDA: Multi-sensor Automatic Threat Identification and Localization with Deep-learning Architecture
Research funding history
94 SBIR/STTR records share this UEI (1997–2025). Reported award amounts total $50,147,198. Reported amounts are not federal obligations.
Phases: Phase I, Phase II, Phase II – Direct to Phase II
Agencies: Department of Defense, National Science Foundation, Department of Energy, National Aeronautics and Space Administration