Comparative study finds CNNs robust on small datasets for land use classification while Vision Transformers perform better on global spatial relationships when sufficient training data is available.
Vision transformer for remote sensing image classification: A review,
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.CV 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Vision Transformers and Convolutional Neural Networks for Land Use Scene Classification
Comparative study finds CNNs robust on small datasets for land use classification while Vision Transformers perform better on global spatial relationships when sufficient training data is available.