SBIR/STTR Research Award
Statistical Characterization and Operation Readiness assessment of ELINT/SIGINT Deep learning (SCORED)
Award amount
$1,237,464Program and phase
SBIR · Phase IIAward year
2023Award details
- Awarding agency
- Department of Defense
- Branch
- Air Force
- Recipient company
- MACHINA COGNITA TECHNOLOGIES, INC.
- Proposal award date
- 2023-09-21
- Contract end date
- 2025-09-20
- UEI
- MP37XZUHS7C3
- Solicitation number
- 22.1
- Topic code
- AF221-0022
Research abstract
The application of advances in Machine Learning and in particular Deep Learning (DL) to complex RF applications provides a great opportunity to advance DoD system capabilities. However, the black box nature of DL models requires additional advances in Exp
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.
- Natural-language Ontologies for battlespace Visualizations and Analytics (NOVA)
- Marine - eLearning Design and Guidance Engine (Marine-EDGE)
- Automated LLM-based Intelligence Compilation and Evaluation (ALICE)
- Immersive Multi-modal Fusion for Operational Real-time Capability Evaluation (IMFORCE)
- Automated Battle Rhythm Assistant (ABRA)
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- A New Approach to the Testing & Evaluation of Advanced RF Applications of Deep Learning AI
- Reliable AI Explanations for Testing and Evaluation of RF Systems (RAETERS)
- Statistical Characterization and Operation Readiness assessment of ELINT/SIGINT Deep learning (SCORED)
- Applications of Explainability for RF Machine Learning
- A New Approach to the Testing & Evaluation of Advanced RF Applications of Deep Learning AI
Research funding history
17 SBIR/STTR records share this UEI (2020–2026). Reported award amounts total $12,718,041. Reported amounts are not federal obligations.
Phases: Phase I, Phase II
Agencies: Department of Defense