Semantic Segmentation of Aerial Images With Shuffling Convolutional Neural Networks
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DOI: 10.1109/lgrs.2017.2778181
Abstract: Semantic segmentation of aerial images refers to assigning one land cover category to each pixel. This is a challenging task due to the great differences in the appearances of ground objects. Many attempts have been… read more here.
Keywords: neural networks; convolutional neural; semantic segmentation; aerial images ... See more keywords
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
2DSegFormer: 2-D Transformer Model for Semantic Segmentation on Aerial Images
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Geoscience and Remote Sensing"
DOI: 10.1109/tgrs.2022.3223416
Abstract: Two-dimensional position information of input tokens is essential for transformer-based semantic segmentation models, especially on high-resolution aerial images. However, recent transformer-based segmentation methods use position encoding to record position information and most position encoding methods… read more here.
Keywords: semantic segmentation; segmentation aerial; segmentation; transformer model ... See more keywords