Integrated Sensing and Learning with Multi-Modal Sensors
Abstract
A single sensor or sensing modality with an off-the-shelf learning algorithm is insufficient for understanding complex and dynamic environments. As we increase the number of sensors to collect more data, the diversity of data and the storage and computational cost also increase. Processing all the data to extract useful information and present it in ways that can be quickly understood remains a challenging task. To circumvent some of these challenges, we propose to develop an integrated sensing and learning framework for multi-modal sensors.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Jan 21, 2022
- Source ID
- FA95502110330XX0
Entities
People
- M. Salman Asif
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of California Regents