Viewpoint-Aware Capsule Networks for Remote Sensing Scene Classification
A new remote sensing scene classification method is proposed for the viewpoint variation of remote sensing images,the main orientation of each scene class is predicted by a spatial transformation network combined with sensor viewpoint estimation,and the two-dimensional affine transformation parameters are computed inside the network to encode the capsule pose vectors for constructing an equivariant,affine transformation robust primary capsule layer.The intra-class diversity problem of remote sensing images is investigated,sub-concept dynamic routing is proposed to reduce the noisy capsules that appear in subsequent layers and generate an internal compact representation of the scene for remote sensing scene classification.Finally,tests are conducted on two publicly available large remote sensing scene datasets,AID and NWPU-RESISC45,the experimental results demonstrate that the method significantly improves the recognition accuracy of remote sensing scenes.
scene classificationcapsule networkpose proposalsub-conceptdynamic routing
国家科技期刊平台
NSTL
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