Abstract
A cost-aware Bayesian sequential decision-making strategy for domain search and object classification using a limited-range sensor is presented. On one hand, it is risky to allocate all available sensing resources at a single location while ignoring other regions. On the other hand, the sensor may miss-detect or miss-classify a critical object with insufficient observations. Therefore, we develop a decision-making strategy that balances the tolerable risks and the desired decision precision under limited resources.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: IEEE Transactions on Aerospace and Electronic Systems
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
