A New CBAM-P-Net Model for Few-Shot Forest Species Classification Using Airborne Hyperspectral Images

A New CBAM-P-Net Model for Few-Shot Forest Species Classification Using Airborne Hyperspectral Images

High-precision automatic identification and mapping of forest tree species composition is an important content of forest resource survey and monitoring. The airborne hyperspectral image contains rich spectral and spatial information, which provides the possibility of high-precision classification an...

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Bibliographic Details
Main Authors: Long Chen, Xiaomin Tian, Guoqi Chai, Xiaoli Zhang, Erxue Chen
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Remote Sensing
Subjects:
airborne hyperspectral images
tree species classification
prototypical networks
few-shot learning
CBAM-P-Net
Online Access:https://www.mdpi.com/2072-4292/13/7/1269

Internet

https://www.mdpi.com/2072-4292/13/7/1269

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