no code implementations • 7 Oct 2020 • Yun Cao, Yuebin Wang, Junhuan Peng, Liqiang Zhang, Linlin Xu, Kai Yan, Lihua Li
With a small number of labeled samples for training, it can save considerable manpower and material resources, especially when the amount of high spatial resolution remote sensing images (HSR-RSIs) increases considerably.
no code implementations • 7 Oct 2020 • Yun Cao, Jie Mei, Yuebin Wang, Liqiang Zhang, Junhuan Peng, Bing Zhang, Lihua Li, Yibo Zheng
In SLCRF, first, the 3D convolutional autoencoder (3DCAE) is introduced to remove the redundant information in HSI pixels.
1 code implementation • 1 Oct 2020 • Xiaoman Qi, PanPan Zhu, Yuebin Wang, Liqiang Zhang, Junhuan Peng, Mengfan Wu, Jialong Chen, Xudong Zhao, Ning Zang, P. Takis Mathiopoulos
Few multi-label high spatial resolution remote sensing datasets have been developed to train deep learning models for multi-label based tasks, such as scene classification and image retrieval.