TINYCD: a (not so) deep learning model for change detection
Author:
Funder
SEA Vision s.r.l.
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-022-08122-3.pdf
Reference71 articles.
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3. Bai T, Wang L, Yin D, Sun K, Chen Y, Li W, Li D (2022) Deep learning for change detection in remote sensing: a review. Geo-spat Inf Sci. https://doi.org/10.1080/10095020.2022.2085633
4. Chen H, Shi Z (2020) A spatial-temporal attention-based method and a new dataset for remote sensing image change detection. Remote Sens 12(10):1662
5. De Bem PP, de Carvalho Junior OA, Fontes Guimarães R, Trancoso Gomes RA (2020) Change detection of deforestation in the brazilian amazon using landsat data and convolutional neural networks. Remote Sens 12(6):901
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