Bayesian Nonparametric Learning and Knowledge Transfer for Object Tracking Under Unknown Time-Varying Conditions
We consider the problem of a primary source tracking a moving object under time-varying and unknown noise conditions. We propose two methods that integrate sequential Bayesian filtering with transfer learning to improve tracking performance. Within the transfer learning framework, multiple sources a...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2022-07-01
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| Series: | Frontiers in Signal Processing |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/frsip.2022.868638/full |