Multispectral image classification method based on surface wave CNN
A multi-spectral image and classification method technology, applied in the field of multi-spectral image classification based on surface wave CNN, can solve the problem of multi-spectral image multi-scale, multi-direction, multi-resolution characteristics, multi-spectral image is difficult to get higher classification Accuracy and other issues to achieve the effect of improving classification accuracy
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[0070] Example
[0071] 1. Simulation conditions:
[0072] The hardware platform is: Intel(R) Xeon(R) CPU E5650@2.13GHz Multi-spectral image classification method based on multi-scale depth filter
[0073] Graphics card: Quadro K2200 / PCIe / SSE2, 2.40GHz Multispectral image classification method based on multiscale depth filter
[0074] Memory: 8G
[0075] The software platform is: Caffe.
[0076] 2. Simulation content and results:
[0077] The method of the present invention is used to conduct experiments under the above simulation conditions, that is, 5% of marked pixels are randomly selected from each category of multispectral data as training samples, and the entire image is used as test data, and the following results are obtained: image 3 classification results.
[0078] from image 3 It can be seen that the regional consistency of the classification results is good, the edges of different regions are also very clear, and the detailed information is maintained.
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