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OpenForest: A data catalogue for machine learning in forest monitoring
v1v2 (latest)

OpenForest: A data catalogue for machine learning in forest monitoring

1 November 2023
Arthur Ouaknine
T. Kattenborn
Etienne Laliberté
David Rolnick
ArXiv (abs)PDFHTMLGithub (181★)

Papers citing "OpenForest: A data catalogue for machine learning in forest monitoring"

4 / 4 papers shown
Title
GlobalGeoTree: A Multi-Granular Vision-Language Dataset for Global Tree Species Classification
GlobalGeoTree: A Multi-Granular Vision-Language Dataset for Global Tree Species Classification
Yang Mu
Zhitong Xiong
Yi Wang
Muhammad Shahzad
Franz Essl
Mark van Kleunen
Xiao Xiang Zhu
VLM
112
0
0
18 May 2025
Contrastive ground-level image and remote sensing pre-training improves
  representation learning for natural world imagery
Contrastive ground-level image and remote sensing pre-training improves representation learning for natural world imagery
Andy V. Huynh
Lauren E. Gillespie
Jael Lopez-Saucedo
Claire Tang
Rohan Sikand
Moisés Expósito-Alonso
SSL
127
5
0
28 Sep 2024
Insect Identification in the Wild: The AMI Dataset
Insect Identification in the Wild: The AMI Dataset
Aditya Jain
Fagner Cunha
M. Bunsen
Juan Sebastián Canas
L. Pasi
...
K. P. McFarland
David Roy
T. Høye
Maxim Larrivée
David Rolnick
104
5
0
18 Jun 2024
PureForest: A Large-Scale Aerial Lidar and Aerial Imagery Dataset for
  Tree Species Classification in Monospecific Forests
PureForest: A Large-Scale Aerial Lidar and Aerial Imagery Dataset for Tree Species Classification in Monospecific Forests
Charles Gaydon
Floryne Roche
97
4
0
18 Apr 2024
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