Multi-Label Noise Robust Collaborative Learning for Remote Sensing Image Classification. (arXiv:2012.10715v6 [eess.IV] UPDATED)

The development of accurate methods for multi-label classification (MLC) of
remote sensing (RS) images is one of the most important research topics in RS.
The MLC methods based on convolutional neural networks (CNNs) have shown strong
performance gains in RS. However, they usually require a high number of
reliable training images annotated with multiple land-cover class labels.
Collecting such data is time-consuming and costly. To address this problem, the
publicly available thematic products, which can include noisy labels, can be …

arxiv classification collaborative image noise remote sensing