A new aircraft classification algorithm based on sum pooling feature with remote sensing image

Binzhe Li; Jing Hu; Li Fang; SuSu Kang; XiangJun Li

doi:10.1117/12.2541853

14 February 2020 A new aircraft classification algorithm based on sum pooling feature with remote sensing image

Binzhe Li, Jing Hu, Li Fang, SuSu Kang, XiangJun Li

Proceedings Volume 11430, MIPPR 2019: Pattern Recognition and Computer Vision; 114301U (2020) https://doi.org/10.1117/12.2541853
Event: Eleventh International Symposium on Multispectral Image Processing and Pattern Recognition (MIPPR2019), 2019, Wuhan, China

Abstract

For the problem that VGG network cannot use the special information of feature maps, this paper proposes a new algorithm that constructs the sum pooling feature based on the feature map extracted by the convolutional neural network. And this algorithm retains the construction of original feature maps so that special information on the original feature map could be used more reasonably. And then, this paper uses DOTA datasets to verify the proposed method. The results show that compared with the VGG-16 network, the proposed SPFC algorithm improves the accuracy in rough aircraft classification and the fighter subdivision.

Citation Download Citation

Binzhe Li, Jing Hu, Li Fang, SuSu Kang, and XiangJun Li "A new aircraft classification algorithm based on sum pooling feature with remote sensing image", Proc. SPIE 11430, MIPPR 2019: Pattern Recognition and Computer Vision, 114301U (14 February 2020); https://doi.org/10.1117/12.2541853

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