Remote Sensing Scene Classification Using Multilayer Stacked Covariance Pooling.

IEEE Transactions on Geoscience and Remote Sensing(2018)

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摘要
This paper proposes a new method, called multilayer stacked covariance pooling (MSCP), for remote sensing scene classification. The innovative contribution of the proposed method is that it is able to naturally combine multilayer feature maps, obtained by pretrained convolutional neural network (CNN) models. Specifically, the proposed MSCP-based classification framework consists of the following t...
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关键词
Feature extraction,Remote sensing,Nonhomogeneous media,Support vector machines,Covariance matrices,Computational modeling,Semantics
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