DIAL: Deep Interactive and Active Learning for Semantic Segmentation in Remote Sensing. (arXiv:2201.01047v1 [cs.CV])

We propose in this article to build up a collaboration between a deep neural
network and a human in the loop to swiftly obtain accurate segmentation maps of
remote sensing images. In a nutshell, the agent iteratively interacts with the
network to correct its initially flawed predictions. Concretely, these
interactions are annotations representing the semantic labels. Our
methodological contribution is twofold. First, we propose two interactive
learning schemes to integrate user inputs into deep neural networks. The first
one concatenates …

active learning arxiv cv interactive learning remote segmentation semantic sensing