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kl
- 基于bp神经网络的遥感图像的分类和识别的MATLAB实现-Bp neural network-based remote sensing image classification and recognition of the MATLAB implementation
SOM
- 基于matlab的自组织神经网络进行遥感图像分类处理-Matlab based on the self-organizing neural network for remote sensing image classification processing
cal_class
- 利用最大似然法，通过感兴趣区域对遥感图像进行分类-Using the maximum likelihood method, by region of interest on remote sensing image classification
fenlei
- 利用深度学习进行遥感图像场景分类 这里我们对NWPU-RESISC45数据集的场景图像进行分类 我们将卷积神经网络应用于图像分类。我们从头开始训练数据集。此外，还应用了预先训练的VGG16 abd ResNet50进行迁移学习。(Scene Classification of Remote Sensing Images Using Deep Learning Here we classify scene images from NWPU-RESISC45 dataset We apply
MATLAB
- 实现遥感图像地物分类，利用了BP神经网络，结果清晰功能强大(Realization of Ground Object Classification in Remote Sensing Images)
exp1
- matlab实现最大似然法的遥感图像分类，数据以excel形式给出(MATLAB realizes the classification of remote sensing images by maximum likelihood method, and the data are given in Excel form)