Remote sensing image recognition method based on feature aggregation convolutional network
A convolutional network and remote sensing image technology, applied in the field of remote sensing image recognition, can solve problems such as too little training set data, difficulty in training convolutional neural networks, etc., and achieve the effect of improving accuracy.
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[0041] like figure 1 As shown, the remote sensing scene recognition method based on feature aggregation convolutional network provided by the present invention mainly includes the following steps:
[0042] 1) Use the VGG-16 convolutional neural network to extract features;
[0043] Use the convolutional layer, downsampling layer, fully connected layer, and activation function layer to build the VGG-16 convolutional neural network framework, and use the different convolutional layers of VGG-16 to extract the convolutional features of remote sensing images;
[0044] 2) Convolution feature encoding;
[0045] Construct a deep convolutional feature encoding module, which can be embedded into the VGG-16 convolutional neural network to fuse the spatial information and semantic information of different convolutional features, and encode the convolutional features of different convolutional layers into convolutional Express;
[0046] 3) Remote sensing scene expression;
[0047] The...
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