Uncertainty from Motion for DNN Monocular Depth Estimation
Deployment of deep neural networks (DNNs) for monocular depth estimation in safety-critical scenarios on resource-constrained platforms requires well-calibrated and efficient uncertainty estimates. However, many popular uncertainty estimation techniques, including state-of-the-art ensembles and p...
| Main Authors: | , , |
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| Format: | Article |
| Published: |
2022
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| Online Access: | https://hdl.handle.net/1721.1/141382 |