TreeFormer: a Semi-Supervised Transformer-based Framework for Tree
Counting from a Single High Resolution Image

TreeFormer: a Semi-Supervised Transformer-based Framework for Tree Counting from a Single High Resolution Image

IEEE Transactions on Geoscience and Remote Sensing (TGRS), 2023

12 July 2023

H. A. Amirkolaee

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Papers citing "TreeFormer: a Semi-Supervised Transformer-based Framework for Tree Counting from a Single High Resolution Image"

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Title
OAM-TCD: A globally diverse dataset of high-resolution tree cover maps Josh Veitch-Michaelis Andrew Cottam Daniella Schweizer Eben N. Broadbent David Dao Ce Zhang Angélica María Almeyda Zambrano Simeon Max 143 7 0 16 Jul 2024
AdaTreeFormer: Few Shot Domain Adaptation for Tree Counting from a Single High-Resolution ImageIsprs Journal of Photogrammetry and Remote Sensing (ISPRS J. Photogramm. Remote Sens.), 2024 H. A. Amirkolaee Miaojing Shi Lianghua He Mark Mulligan 306 4 0 05 Feb 2024
OpenForest: A data catalogue for machine learning in forest monitoringEnvironmental Data Science (EDS), 2023 Arthur Ouaknine T. Kattenborn Etienne Laliberté David Rolnick 430 14 0 01 Nov 2023