Remote sensing scene classification with multi-spatial scale frequency covariance pooling-Reference-Cited by-同舟云学术

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Remote sensing scene classification with multi-spatial scale frequency covariance pooling

Published:2022-04-06 Issue:21 Volume:81 Page:30413-30435
ISSN:1380-7501
Container-title:Multimedia Tools and Applications
language:en
Short-container-title:Multimed Tools Appl

Author:

Chen Wenjie,Gao Yuan,Chen Aibin^ORCID,Zhou Guoxiong,Wang Jianwu,Yang Xiaobo,Jiang RunDong

Funder

the National 948 Project of China: Forest Fire Prediction and Fire Fighting Resource Dispatching Technology

National Natural Science Foundation of China

the Hunan Provincial Natural Science Foundation of China

Graduate Innovation Fund of Central South University of Forestry and Technology

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Hardware and Architecture,Media Technology,Software

Link

https://link.springer.com/content/pdf/10.1007/s11042-022-12603-x.pdf

Reference45 articles.

1. Chaib S, Gu Y, Yao H (2015) An informative feature selection method based on sparse PCA for VHR scene classification[J]. IEEE Geosci Remote Sens Lett 13(2):147–151. https://doi.org/10.1109/lgrs.2015.2501383

2. Chan TH, Jia K, Gao S (2015) PCANet: a simple deep learning baseline for image classification?[J]. IEEE Trans Image Process 24(12):5017–5032. https://doi.org/10.1109/tip.2015.2475625

3. Chen Y, Fang H, Xu B (2019) Drop an octave: reducing spatial redundancy in convolutional neural networks with octave convolution[J]. arXiv preprint arXiv:1904.05049. arXiv:1904.05049v3

4. Cheng G, Guo L, Zhao T (2013) Automatic landslide detection from remote-sensing imagery using a scene classification method based on BoVW and pLSA[J]. Int J Remote Sens 34(1):45–59. https://doi.org/10.1080/01431161.2012.705443

5. Cheng G, Han J, Zhou P (2014) Multi-class geospatial object detection and geographic image classification based on collection of part detectors[J]. ISPRS J Photogramm Remote Sens 98:119–132. https://doi.org/10.1016/j.isprsjprs.2014.10.002

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