Corpus ID: 235593296

MEAL: Manifold Embedding-based Active Learning

@article{Sreenivasaiah2021MEALME,
  title={MEAL: Manifold Embedding-based Active Learning},
  author={Deepthi Sreenivasaiah and Thomas Wollmann},
  journal={ArXiv},
  year={2021},
  volume={abs/2106.11858}
}
Image segmentation is a common and challenging task in autonomous driving. Availability of sufficient pixel-level annotations for the training data is a hurdle. Active learning helps learning from small amounts of data by suggesting the most promising samples for labeling. In this work, we propose a new pool-based method for active learning, which proposes promising patches extracted from full image, in each acquisition step. The problem is framed in an exploration-exploitation framework by… Expand

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