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Proceedings Paper

A fast multi-target detection method based on improved YOLO
Author(s): Xiechang Sun; Hao Jiang; Tongtong Huo; Weidong Yang
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Paper Abstract

Detection of sea surface targets in large-scale remote sensing images is one of the important research topics of ocean remote sensing technology. Ocean remote sensing images have the characteristics of wide format, strong interference and small target. This paper adopts the spinning target detection method, and proposes a ship detection model based on YOLO to output the real length, width and axial information. The model can accurately output the position, length and width and axial information of a ship target by predicting the minimum external rectangular area of the ship target, so as to realize multi-target detection and improve the detection performance significantly. To improve the recall rate of the target detection algorithm, this paper adopts the spinning target detection method, and proposes a ship detection model based on YOLO. Through redefining the representation of the rotation matrix and redesigning a new network loss function and the rotated IOU computing method, this model accurately outputs the real length, width and axial information, increases the output feature dimensions, and effectively raises the recall rate and speed of multi-target detection. Lastly, to improve the practicability of the algorithm on mobile devices, the model is processed in a lightweight way. Its parameters are significantly reduced while the detection accuracy is ensured.

Paper Details

Date Published: 14 February 2020
PDF: 8 pages
Proc. SPIE 11429, MIPPR 2019: Automatic Target Recognition and Navigation, 114290Y (14 February 2020); doi: 10.1117/12.2539386
Show Author Affiliations
Xiechang Sun, Institute of Spacecraft Application System Engineering (China)
Hao Jiang, Huazhong Univ. of Science and Technology (China)
Tongtong Huo, Huazhong Univ. of Science and Technology (China)
Weidong Yang, Huazhong Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 11429:
MIPPR 2019: Automatic Target Recognition and Navigation
Jianguo Liu; Hanyu Hong; Xia Hua, Editor(s)

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