Papers about Few-shot Learning / Meta-Learning on Remote Sensing

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Papers about Few-shot Learning / Meta-Learning on Remote Sensing

Scene Classification:

  • Few-Shot Learning For Remote Sensing Scene Classification, Mediterranean and Middle-East Geoscience and Remote Sensing Symposium (M2GARSS), 2020.

  • Meta-Learning for Few-Shot Land Cover Classification, CVPR Workshop, 2020.

  • Few Shot Scene Classification in Remote Sensing using Meta-Agnostic Machine, 2020 6th Conference on Data Science and Machine Learning Applications (CDMA), 2020

Semantic Segmentation:

  • Deep relation network for hyperspectral image few-shot classification, Remote Sensing, 2020.

  • Deep Transfer Learning for Few-Shot SAR Image Classification, Remote Sensing, 2019.

  • Sar image classification using few-shot cross-domain transfer learning, CVPR Workshop, 2019.

  • Deep few-shot learning for hyperspectral image classification, TGRS, 2018.

  • Low-shot learning for the semantic segmentation of remote sensing imagery, TGRS, 2018.

Object Detection:

  • Few-shot Object Detection on Remote Sensing Images, arxiv, 2020.

  • A training-free, one-shot detection framework for geospatial objects in remote sensing images, IGARSS, 2019.

  • Meta-SSD: Towards fast adaptation for few-shot object detection with meta-learning, IEEE Access, 2019.