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Found 2 papers, 2 papers with code
MUS-CDB: Mixed Uncertainty Sampling with Class Distribution Balancing for Active Annotation in Aerial Object Detection
However, existing active learning methods are mainly with class-balanced settings and image-based querying for generic object detection tasks, which are less applicable to aerial object detection scenarios due to the long-tailed class distribution and dense small objects in aerial scenes.
ALiPy: Active Learning in Python
Supervised machine learning methods usually require a large set of labeled examples for model training.
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