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利用U-Net和选择性特征提取用于使用遥感图像进行土地覆盖分类

Leo Thomas Ramos1,2, Angel D Sappa3,4

  • 1Computer Vision Center, Universitat Autònoma de Barcelona, Barcelona, 08193, Spain. ltramos@cvc.uab.cat.

Scientific reports
|January 4, 2025
PubMed
概括

这项研究增强了U-Net使用SK-ResNeXt进行土地覆盖分类,提高了多光谱成像的准确性. 新模型在细分复杂的土地覆盖类型方面表现出色,优于现有方法.

关键词:
计算机视觉 计算机视觉 计算机视觉图像细分 图像细分 图像细分土地覆盖的分类 土地覆盖的分类多光谱成像技术的使用.遥感是一种远程传感.语义细分 语义细分是指语义细分.

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