MineDL: Efficient Mine Detection and Localization Using Advanced YOLO and LSTM with Few-Shot Learning
Award amount
$140,000Program and phase
SBIR · Phase IAward year
2024Award details
- Awarding agency
- Department of Defense
- Branch
- Navy
- Recipient company
- INFOBEYOND TECHNOLOGY LLC
- Proposal award date
- 2024-09-09
- Contract end date
- 2025-03-08
- UEI
- JMXHCAK12LZ7
- Solicitation number
- 24.1
- Topic code
- N241-025
Research abstract
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.
- MsObjDET: AI-based Multi-Spectral Passive Object Detection using Spatiotemporal Transformer and YOLO with Dynamic Tracking Integration
- GANWave: GAN-enabled OFDM High Capacity Waveform for Low Identification and Detection Probability with Energy Efficiency and Security
- AI-Fire: Advanced Fire Ignition Video Analysis through Multimodal Spatiotemporal Detection & Localization Using Transformer-Enhanced YOLO
- UnifiedDL: Secure Metadata-enabled Intelligent Data Integration and Management Lake by AI-powered Graph Canonization and Parallel Processing
- OT-Healer: A Real-time Decentralized Self-Security/Healing Tool for DER OT Resiliency
Awards with the same topic code
Verified by an exact topic code match. This is not a text-similarity match.
- Sonar Adapted Low-shot Model for Ordnance Neutralization
- AAI/MLT for ATR USing small/reduced Data sets
- MARINE MINED: FEW-SHOT LEARNING FOR UNDERSEA MINE COUNTERMEASURES (MCM)
- Low-shot Algorithm for Mine Data Augmentation (LAMDA)
Research funding history
44 SBIR/STTR records share this UEI (2010–2025). Reported award amounts total $13,013,950. Reported amounts are not federal obligations.
Phases: Phase I, Phase II
Agencies: Department of Defense, Department of Energy, Department of Commerce, Department of Transportation