Mfpenet: multistage foreground-perception enhancement network for remote-sensing scene classification-Reference-Cited by-同舟云学术

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Mfpenet: multistage foreground-perception enhancement network for remote-sensing scene classification

Published:2024-08-13 Issue: Volume: Page:
ISSN:0178-2789
Container-title:The Visual Computer
language:en
Short-container-title:Vis Comput

Author:

Sun Junding,Wang Chenxu,Sima Haifeng,Wu Xiaosheng,Wang Shuihua,Zhang Yudong

Funder

National Natural Science Foundation

Nationally Funded Postdoctoral Researcher Program

Key Science and Technology Program of Henan Province

MRC

Royal Society

BHF

Hope Foundation for Cancer Research

GCRF

Sino-UK Industrial Fund

LIAS

Data Science Enhancement Fund

Fight for Sight

Sino-UK Education Fund

BBSRC

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s00371-024-03587-w.pdf

Reference55 articles.

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2. Cheng, G., Guo, L., Zhao, T., Han, J., Li, H., Fang, J.: Automatic landslide detection from remote-sensing imagery using a scene classification method based on bovw and plsa. Int. J. Remote Sens. 34(1), 45–59 (2013). https://doi.org/10.1080/01431161.2012.705443

3. Li, J., Chen, J., Sheng, B., Li, P., Yang, P., Feng, D.D., Qi, J.: Automatic detection and classification system of domestic waste via multimodel cascaded convolutional neural network. IEEE Trans. Ind. Inform. 18(1), 163–173 (2021). https://doi.org/10.1109/TII.2021.3085669

4. Liu, Y., Xiong, Z., Yuan, Y., Wang, Q.: Distilling knowledge from super resolution for efficient remote sensing salient object detection. IEEE Trans. Geosci. Remote Sens. (2023). https://doi.org/10.1109/TGRS.2023.3267271

5. Jones, J.W.: Improved automated detection of subpixel-scale inundation-revised dynamic surface water extent (dswe) partial surface water tests. Remote Sens. 11(4), 374 (2019). https://doi.org/10.3390/rs11040374

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