/Cross-HL

Pytorch implementation of the Cross-HL attention transformer model

Primary LanguageJupyter Notebook

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

Sample Dataset

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.

Citation

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 = {}
}