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Found 2 papers, 1 papers with code
Evaluating Self and Semi-Supervised Methods for Remote Sensing Segmentation Tasks
We find that such techniques significantly improve generalization performance when labeled data is limited and there are geographic domain shifts between the training data and the validation/test data.
No Modes left behind: Capturing the data distribution effectively using GANs
Given a set of data that has an imbalance in the distribution, the networks are susceptible to missing modes and not capturing the data distribution.
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