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How Active Learning Can Improve Your Computer Vision Pipeline

DagsHub

DECEMBER 23, 2024

It operates on a large static pool of unlabeled data and selectively chooses the most informative samples for labeling. Traditional Active Learning has the following characteristics. Relies on explicit decision boundaries or feature representations for sample selection. Libact : It is a Python package for active learning.

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How Active Learning Can Improve Your Computer Vision Pipeline

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