Multiscale Attention Feature Fusion Based on Improved Transformer for Hyperspectral Image and LiDAR Data Classification

Multiscale Attention Feature Fusion Based on Improved Transformer for Hyperspectral Image and LiDAR Data Classification

With the uninterrupted evolution of remote sensing data, the list of available data sources has expanded, effectively utilizing useful information from multiple sources for better land surface observation, which has become an intriguing and challenging problem. However, the complexity of urban areas...

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Bibliographic Details
Main Authors: Aili Wang, Guilong Lei, Shiyu Dai, Haibin Wu, Yuji Iwahori
Format: Article
Language:English
Published: IEEE 2025-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Hyperspectral image (HSI)
interaction transformer
light detection and ranging (LiDAR)
multisource data classification
three-dimensional convolutional neural network (3D-CNN)
Online Access:https://ieeexplore.ieee.org/document/10818716/
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