Cross Hyperspectral and LiDAR Attention Transformer: An Extended Self-Attention for Land Use and Land Cover Classification
Swalpa Kumar Roy, Atri Sukul, Ali Jamali, Juan Mario Haut, and Pedram Ghamisi
The repository contains the implementations for Cross Hyperspectral and LiDAR Attention Transformer: An Extended Self-Attention for Land Use and Land Cover Classification
Get the disjoint dataset (TrentoDataset folder) from Google Drive.
Get the disjoint dataset (HoustonDataset folder) from Google Drive.
Get the disjoint dataset (MUUFL_Dataset folder) from Google Drive.
Please kindly cite the papers if this code is useful and helpful for your research.
@article{roy2022crosshl,
title={Cross Hyperspectral and LiDAR Attention Transformer: An Extended Self-Attention for Land Use and Land Cover Classification},
author={Roy, Swalpa Kumar and Sukul, Atri and Jamali, Ali and Haut, Juan Mario and Ghamisi, Pedram},
journal={IEEE Transactions on Geoscience and Remote Sensing},
volume = {},
year={2024},
doi = {}
}