A Weakly-Supervised Change Detection Technique for SAR Images Based on Deep Learning and Synthetic Training Data Generated by an Ensemble of Self-Organizing Maps

Victor-Emil Neagoe, Adrian-Dumitru Ciotec, Lorenzo Bruzzone. A Weakly-Supervised Change Detection Technique for SAR Images Based on Deep Learning and Synthetic Training Data Generated by an Ensemble of Self-Organizing Maps. In 2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019, Yokohama, Japan, July 28 - August 2, 2019. pages 1669-1672, IEEE, 2019. [doi]

@inproceedings{NeagoeCB19,
  title = {A Weakly-Supervised Change Detection Technique for SAR Images Based on Deep Learning and Synthetic Training Data Generated by an Ensemble of Self-Organizing Maps},
  author = {Victor-Emil Neagoe and Adrian-Dumitru Ciotec and Lorenzo Bruzzone},
  year = {2019},
  doi = {10.1109/IGARSS.2019.8898344},
  url = {https://doi.org/10.1109/IGARSS.2019.8898344},
  researchr = {https://researchr.org/publication/NeagoeCB19},
  cites = {0},
  citedby = {0},
  pages = {1669-1672},
  booktitle = {2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019, Yokohama, Japan, July 28 - August 2, 2019},
  publisher = {IEEE},
  isbn = {978-1-5386-9154-0},
}