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Deep learning framework for hyperspectral image classification

Python 100.00%

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有个问题想问您一下，用Unlabeled Data之后，再用labeled Data时训练是进行一个网络参数的微调吗？
我个人理解思路是使用未标记图像训练，然后用标记图像进行训练调整网络参数，这样就扩充了训练样本，感觉是个很好的思路，受到您的启发，不知道我理解的对不对
但是如果未标记图像训练时标记为16类，那这16类是怎么得到的呢，和待验证图像的类别会不会差别大，毕竟未标记图像和待测试图像可能来自不同传感器，如果使用相同传感器的未标签图像来预训练会不会好一点。
以上纯属个人浅显的想法。
不好意思，多有打扰，祝好

您好，请问您的这个实验有论文吗？

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