(FY22 YIP) ADVERSARIAL SENSING- A SELF-SUPERVISED APPROACH TO AI-BASED MULTIMODAL SENSOR FUSION
Abstract
Significantly improved USAF situational awareness and intelligence gathering capabilities- Time-varying neural signal representations (as opposed to fixed pixel or voxel representations) will allow us to effectively fuse information from measurements captured at different times – resulting in a multiplicative improvement in signal-to-noise ratios. Meanwhile, the overall adversarial sensing framework will enable effective multimodal sensor fusion in situations where one does not have access to training data.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Mar 07, 2023
- Source ID
- FA95502210208
Entities
People
- Christopher A. Metzler
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Maryland