Spatial Coherence-Based Batch-Mode Active Learning for Remote Sensing Image Classification

@article{Shi2015SpatialCB,
  title={Spatial Coherence-Based Batch-Mode Active Learning for Remote Sensing Image Classification},
  author={Qian Shi and Bo Du and Liangpei Zhang},
  journal={IEEE Transactions on Image Processing},
  year={2015},
  volume={24},
  pages={2037-2050}
}
Batch-mode active learning (AL) approaches are dedicated to the training sample set selection for classification, regression, and retrieval problems, where a batch of unlabeled samples is queried at each iteration by considering both the uncertainty and diversity criteria. However, for remote sensing applications, the conventional methods do not consider the spatial coherence between the training samples, which will lead to the unnecessary cost. Based on the above two points, this paper… CONTINUE READING

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