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Found 3 papers, 1 papers with code
Integrating Multiple Sources Knowledge for Class Asymmetry Domain Adaptation Segmentation of Remote Sensing Images
Firstly, a multi-branch segmentation network is built to learn an expert for each source RSI.
Unsupervised Meta Learning With Multiview Constraints for Hyperspectral Image Small Sample set Classification
However, the existing methods based on meta learning still need to construct a labeled source data set with several pre-collected HSIs, and must utilize a large number of labeled samples for meta-training, which is actually time-consuming and labor-intensive.
Active Deep Densely Connected Convolutional Network for Hyperspectral Image Classification
First, a deep densely connected convolutional network is considered for hyperspectral image classification.
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