Improving Semantic Segmentation in Aerial Imagery via Graph Reasoning and Disentangled Learning
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DOI: 10.1109/tgrs.2021.3121471
Abstract: Semantic segmentation in aerial imagery is still an important, yet challenging task due to the complex characteristics of remote-sensing data. The critical issues consist of: 1) extreme foreground–background imbalance; 2) large intra-class variance; and 3)… read more here.
Keywords: aerial imagery; segmentation aerial; via graph; disentangled learning ... See more keywords