Active Video Hashing via Structure Information Learning for Activity Analysis
When attempting to analyze and understand large-scale video datasets, choosing training videos using active learning can significantly reduce the annotation costs associated with supervised learning without sacrificing the accuracy of classifiers. However, to further reduce the computational overhea...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9093899/ |