Transformers in Remote Sensing: A Survey

Transformers in Remote Sensing: A Survey

Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformer-based architectures, originally introduced in natural language processing, have pervaded computer vision field where the self-attention mechan...

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Bibliographic Details
Published in:Remote sensing (Basel, Switzerland) Vol. 15; no. 7; p. 1860
Main Authors: Aleissaee, Abdulaziz Amer, Kumar, Amandeep, Anwer, Rao Muhammad, Khan, Salman, Cholakkal, Hisham, Xia, Gui-Song, Khan, Fahad Shahbaz
Format: Journal Article
Language:English
Published: Basel MDPI AG 01-03-2023
Subjects:
Algorithms
Analysis
Artificial satellites in remote sensing
Classification
Computational linguistics
Computer vision
Deep learning
Environmental science
Image analysis
Image processing
Language processing
Machine learning
Machine vision
Medical imaging
Methods
Natural language interfaces
Natural language processing
Polls & surveys
Radar imaging
Remote sensing
Sensors
Soil sciences
Spectrum analysis
survey
Surveys
Synthetic aperture radar
transformers
United Arab Emirates
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Summary:Deep learning-based algorithms have seen a massive popularity in different areas of remote sensing image analysis over the past decade. Recently, transformer-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, the remote sensing community has also witnessed an increased exploration of vision transformers for a diverse set of tasks. Although a number of surveys have focused on transformers in computer vision in general, to the best of our knowledge we are the first to present a systematic review of recent advances based on transformers in remote sensing. Our survey covers more than 60 recent transformer-based methods for different remote sensing problems in sub-areas of remote sensing: very high-resolution (VHR), hyperspectral (HSI) and synthetic aperture radar (SAR) imagery. We conclude the survey by discussing different challenges and open issues of transformers in remote sensing.
ISSN:2072-4292
2072-4292
DOI:10.3390/rs15071860