Semisupervised heterogeneous ensemble for ship target discrimination in synthetic aperture radar images
Author:
Publisher
Springer Science and Business Media LLC
Subject
Aquatic Science,Oceanography
Link
https://link.springer.com/content/pdf/10.1007/s13131-021-1980-2.pdf
Reference51 articles.
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2. Aiello M, Vezzoli R, Gianinetto M. 2019. Object-based image analysis approach for vessel detection on optical and radar images. Journal of Applied Remote Sensing, 13(1): 014502
3. Albukhanajer W A, Jin Yaochu, Briffa J A. 2017. Classifier ensembles for image identification using multi-objective Pareto features. Neurocomputing, 238: 316–327, doi: https://doi.org/10.1016/j.neucom.2017.01.067
4. Amozegar M, Khorasani K. 2016. An ensemble of dynamic neural network identifiers for fault detection and isolation of gas turbine engines. Neural Networks, 76: 106–121, doi: https://doi.org/10.1016/j.neunet.2016.01.003
5. Ao Wei, Xu Feng, Li Yongchen, et al. 2018. Detection and discrimination of ship targets in complex background from spaceborne ALOS-2 SAR images. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 11(2): 536–550, doi: https://doi.org/10.1109/JSTARS.2017.2787573
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