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Proceedings Paper

Accurate detection of berthing ship target based on mask R-CNN
Author(s): Yu Zhang; Yan Zhang; Shu-Xin Li; Jing-Hua Zhang
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Paper Abstract

This paper mainly studies the berthing ship target detection method of overhead-view image under the condition of a few training samples. Because of the limited training samples, we use the complete data set unrelated to the target detection task for pre-training to obtain a classification model, then expand the data according to a certain percentage and finally complete the training of the target detection model. This paper uses the idea of segmentation to solve the target detection problem. We adjusted the configuration of the region proposal network including the size of anchor frame and the threshold of non-maximum suppression according to the target morphology, so that the network generates a more accurate region of interest. Finally, the confidence levels, bounding-boxes and image masks of multi-objective generated concurrently. We performed experiments on self-made data sets which labeled from NWPU VHR-10 and produced good results, which proved the feasibility of this method in target detection of berthing ship target.

Paper Details

Date Published: 29 October 2018
PDF: 9 pages
Proc. SPIE 10836, 2018 International Conference on Image and Video Processing, and Artificial Intelligence, 1083602 (29 October 2018); doi: 10.1117/12.2326820
Show Author Affiliations
Yu Zhang, National Univ. of Defense Technology (China)
Yan Zhang, National Univ. of Defense Technology (China)
Shu-Xin Li, National Univ. of Defense Technology (China)
Jing-Hua Zhang, National Univ. of Defense Technology (China)


Published in SPIE Proceedings Vol. 10836:
2018 International Conference on Image and Video Processing, and Artificial Intelligence
Ruidan Su, Editor(s)

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