Semantic Labeling of High Resolution Images Using EfficientUNets and Transformers. (arXiv:2206.09731v2 [cs.CV] UPDATED)

Web: http://arxiv.org/abs/2206.09731

Semantic segmentation necessitates approaches that learn high-level
characteristics while dealing with enormous amounts of data. Convolutional
neural networks (CNNs) can learn unique and adaptive features to achieve this
aim. However, due to the large size and high spatial resolution of remote
sensing images, these networks cannot analyze an entire scene efficiently.
Recently, deep transformers have proven their capability to record global
interactions between different objects in the image. In this paper, we propose
a new segmentation model that combines convolutional …

arxiv cv images labeling semantic transformers