Utilizing active learning and attention-CNN to classify vegetation based on UAV multispectral data

Utilizing active learning and attention-CNN to classify vegetation based on UAV multispectral data

Abstract This paper presents a deep learning model based on an active learning strategy. The model achieves accurate identification of vegetation types in the study area by utilizing multispectral data obtained from preprocessing of unmanned aerial vehicle (UAV) remote sensing equipment. This approa...

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Bibliographic Details
Main Authors: Sheng Miao, Chuanlong Wang, Guangze Kong, Xiuhe Yuan, Xiang Shen, Chao Liu
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
Subjects:
UAV remote sensing
Convolutional neural network
Convolutional block attention module
Gated fully fusion
Vegetation classification
Online Access:https://doi.org/10.1038/s41598-024-82248-3
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https://doi.org/10.1038/s41598-024-82248-3

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