Loop Closure Detection Based on Compressed ConvNet Features in Dynamic Environments
In dynamic environments, convolutional neural networks (CNNs) often produce image feature maps with significant redundancy due to external factors such as moving objects and occlusions. These feature maps are inadequate as precise image descriptors for similarity measurement, hindering loop closure...
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| Hauptverfasser: | , , |
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| Format: | Artigo |
| Sprache: | Inglês |
| Veröffentlicht: |
MDPI AG
2023-12-01
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| Schriftenreihe: | Applied Sciences |
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| Online-Zugang: | https://www.mdpi.com/2076-3417/14/1/8 |
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