SBIR/STTR Research Award
DETECT-ML: Detection of Energetic Topology Errors via Computed Tomography & Machine Learning
Award amount
$249,891Program and phase
SBIR · Phase IAward year
2023Award details
- Awarding agency
- Department of Defense
- Branch
- Army
- Recipient company
- Compotech, Inc.
- Proposal award date
- 2023-01-11
- Contract end date
- 2023-07-17
- UEI
- N1LRKTJ6FJC3
- Solicitation number
- 22.4
- Topic code
- A224-013
Research abstract
Compotech, Inc. seeks to build on our award winning FRAG-CT munition characterization method by developing a new complementary software and hardware package to provide rapid, real-time defect detection at the heart of a munition’s explosive core. The detection technique leverages proven AI/ML detection software algorithms and high speed CT scanning equipment.
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.
- Large-scale Additive Manufacturing R&D to Advance Modular Shelter Design and Deployment - Phase ll
- Typhoon-resistant Modular, Insulated, Next-generation, All-climate, TSCIF-capable, Off-grid, Rapidly-buildable Structure (MINATORS)
- DETECT-ML: Detection of Energetic Topology Errors via Computed Tomography & Machine Learning - Phase II
- Large-scale Additive Manufacturing R&D to Advance Modular Shelter Design and Deployment
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- AI/ML for Visual Processing of Energetic Defects
- AI for Visual Processing of Energetic Defects
- AI/ML-Enhanced Quantitative X-ray for Rapid Identification of Projectile Fill and Assembly Defects
Research funding history
5 SBIR/STTR records share this UEI (2023–2024). Reported award amounts total $3,282,448. Reported amounts are not federal obligations.
Phases: Phase I, Phase II
Agencies: Department of Defense