Multi-Feature Cross Attention-Induced Transformer Network for Hyperspectral and LiDAR Data Classification

Multi-Feature Cross Attention-Induced Transformer Network for Hyperspectral and LiDAR Data Classification

Transformers have shown remarkable success in modeling sequential data and capturing intricate patterns over long distances. Their self-attention mechanism allows for efficient parallel processing and scalability, making them well-suited for the high-dimensional data in hyperspectral and LiDAR image...

Full description

Bibliographic Details
Main Authors: Zirui Li, Runbang Liu, Le Sun, Yuhui Zheng
Format: Article
Language:English
Published: MDPI AG 2024-07-01
Series:Remote Sensing
Subjects:
hyperspectral imagery
LiDAR data
cross-attention
transformer
classification
Online Access:https://www.mdpi.com/2072-4292/16/15/2775

Internet

https://www.mdpi.com/2072-4292/16/15/2775

Similar Items