Open AccessA real-time detection USV algorithm based on bounding box regression
Author(s) -
Yihong Zhang,
Sicheng Wu,
Zihao Liu,
Yijin Yang,
Daoyun Zhu,
Qian Chen
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1544/1/012022
Subject(s) - intersection (aeronautics) , minimum bounding box , convergence (economics) , computer science , bounding overwatch , set (abstract data type) , algorithm , data set , center (category theory) , real time computing , artificial intelligence , engineering , image (mathematics) , chemistry , crystallography , economic growth , economics , programming language , aerospace engineering
With the rapid development of unmanned surface vessels (USV) applications, USV are widely used in military intelligence collection, target monitoring, and shipping services. However, this also brings security issues to shipping and the country. For more efficient detection of USV, in this paper, an enclosing center distance Intersection over Union (E-CIoU) algorithm is proposed for real-time USV detection, where the normalized distance between center points of the smallest enclosing box and target box is combined with bounding box regression. Meanwhile, we designed a new USV data set. The extensive experiments on USV data set have demonstrated that the proposed approach has achieved better convergence speed during training and a significant accuracy prediction.