MCFTNet: Multimodal Cross-Layer Fusion Transformer Network for Hyperspectral and LiDAR Data Classification
Remote sensing image classification is a popular yet challenging field. Many researchers have combined convolutional neural networks (CNNs) and Transformers for hyperspectral imaging (HSI) classification tasks. However, in traditional Transformers, shallow-level information does not propagate well t...
Saved in:
| Main Authors: | Wei Huang, Tianren Wu, Xueyu Zhang, Liangliang Li, Ming Lv, Zhenhong Jia, Xiaobin Zhao, Hongbing Ma, Gemine Vivone |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10970012/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Multilevel Feature Gated Fusion Based Spatial and Frequency Domain Attention Network for Joint Classification of Hyperspectral and LiDAR Data
by: Cuiping Shi, et al.
Published: (2025-01-01) -
Multimodal Fusion Mamba Network for Joint Land Cover Classification Using Hyperspectral and LiDAR Data
by: Haizhu Pan, et al.
Published: (2025-01-01) -
HCAFNet: Hierarchical Cross-Modal Attention Fusion Network for HSI and LiDAR Joint Classification
by: Jiajia Bai, et al.
Published: (2025-01-01) -
Multiscale Attention Feature Fusion Based on Improved Transformer for Hyperspectral Image and LiDAR Data Classification
by: Aili Wang, et al.
Published: (2025-01-01) -
Estimation of Chlorophyll Content at Stand and Individual Tree Level by UAV Hyperspectral Combined with LiDAR
by: Zhuonan Meng, et al.
Published: (2025-05-01)