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Object detection in remote sensing images based on one-class classification

Abstract : For remote sensing image understanding, target detection is one of the most important tasks. In this paper, we propose one object detection method based on region proposal detection via active contour model and detection based on one-class classification method. The large scale remote sensing image is split into several connected components. And then, the proposed algorithm detects the object from the background. The proposed algorithm has been tested on several scenes of real unmanned aerial vehicle image datasets, and achieves promising results.
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Conference papers
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https://hal-utt.archives-ouvertes.fr/hal-03320741
Contributor : Jean-Baptiste Vu Van Connect in order to contact the contributor
Submitted on : Monday, August 16, 2021 - 1:23:58 PM
Last modification on : Wednesday, October 13, 2021 - 7:16:03 PM

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Tian Wang, Yang Chen, Meina Qiao, Aichun Zhu, Ziyu Wang, et al.. Object detection in remote sensing images based on one-class classification. 2017 Chinese Automation Congress (CAC), Oct 2017, Jinan, China. pp.6583-6587, ⟨10.1109/CAC.2017.8243963⟩. ⟨hal-03320741⟩

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