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Toulouse Hyperspectral Data Set: a benchmark data set to assess
  semi-supervised spectral representation learning and pixel-wise
  classification techniques

Toulouse Hyperspectral Data Set: a benchmark data set to assess semi-supervised spectral representation learning and pixel-wise classification techniques

15 November 2023
R. Thoreau
Laurent Risser
V. Achard
Béatrice Berthelot
X. Briottet
ArXivPDFHTML

Papers citing "Toulouse Hyperspectral Data Set: a benchmark data set to assess semi-supervised spectral representation learning and pixel-wise classification techniques"

3 / 3 papers shown
Title
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial
  Representation Learning
Scale-MAE: A Scale-Aware Masked Autoencoder for Multiscale Geospatial Representation Learning
Colorado Reed
Ritwik Gupta
Shufan Li
S. Brockman
Christopher Funk
Brian Clipp
Kurt Keutzer
Salvatore Candido
M. Uyttendaele
Trevor Darrell
113
165
0
30 Dec 2022
Masked Autoencoders Are Scalable Vision Learners
Masked Autoencoders Are Scalable Vision Learners
Kaiming He
Xinlei Chen
Saining Xie
Yanghao Li
Piotr Dollár
Ross B. Girshick
ViT
TPM
258
7,337
0
11 Nov 2021
Emerging Properties in Self-Supervised Vision Transformers
Emerging Properties in Self-Supervised Vision Transformers
Mathilde Caron
Hugo Touvron
Ishan Misra
Hervé Jégou
Julien Mairal
Piotr Bojanowski
Armand Joulin
283
5,723
0
29 Apr 2021
1