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Transformers in Remote Sensing: A Survey
[article]
2022
arXiv
pre-print
Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformers-based architectures, originally introduced in natural language processing, have pervaded computer vision field where the self-attention mechanism has been utilized as a replacement to the popular convolution operator for capturing long-range dependencies. Inspired by recent advances in computer vision, remote sensing community has also
arXiv:2209.01206v1
fatcat:luchmgyyord5nnjthywqszyj6q