基于深度学习的无人机多光谱遥感影像植被分类

2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE) Pub Date : 2023-01-06 DOI:10.1109/ICCECE58074.2023.10135502

Jiaming Xue, Shanlin Sun, Haimeng Zhao, Wei Chen

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引用次数: 0

摘要

为了为植被检测和地面分类提供可靠的预测模型，利用多光谱无人机图像，基于支持向量机和人工标注相结合的方法，构建了语义分割的多光谱数据集。在此基础上，提出了3D-UNet模型对数据集进行训练，实验结果表明，该模型对验证集的预测率达到89.9%。

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Vegetation Classification of UAV Multispectral Remote Sensing Images Based on Deep Learning

With the aim of providing a reliable prediction model for vegetation detection and ground classification, a multispectral dataset was produced for semantic segmentation, which utilizes multispectral UAV images and is based on a combination of support vector machines and manual annotation. Also, a 3D-UNet model is proposed on which the dataset is trained and experiments show that the model has achieved 89.9 % prediction for the validation set.

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2023 3rd International Conference on Consumer Electronics and Computer Engineering (ICCECE)

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