Robust and real-time automatic target recognition using partial hausdorff distance measure on reconfigurable hardware

Author(s):  
Jinbo Xu ◽  
Yong Dou
2021 ◽  
Vol 13 (18) ◽  
pp. 3555
Author(s):  
Yongcan Yu ◽  
Jianhu Zhao ◽  
Quanhua Gong ◽  
Chao Huang ◽  
Gen Zheng ◽  
...  

To overcome the shortcomings of the traditional manual detection of underwater targets in side-scan sonar (SSS) images, a real-time automatic target recognition (ATR) method is proposed in this paper. This method consists of image preprocessing, sampling, ATR by integration of the transformer module and YOLOv5s (that is, TR–YOLOv5s), and target localization. By considering the target-sparse and feature-barren characteristics of SSS images, a novel TR–YOLOv5s network and a down-sampling principle are put forward, and the attention mechanism is introduced in the method to meet the requirements of accuracy and efficiency for underwater target recognition. Experiments verified the proposed method achieved 85.6% mean average precision (mAP) and 87.8% macro-F2 score, and brought 12.5% and 10.6% gains compared with the YOLOv5s network trained from scratch, and had the real-time recognition speed of about 0.068 s per image.


1998 ◽  
Author(s):  
Haisong Liu ◽  
Minxian Wu ◽  
Guofan Jin ◽  
Gang Cheng ◽  
Qingsheng He

2004 ◽  
Author(s):  
Huaixin Chen ◽  
Jianshe Nan ◽  
Xiaosun Li ◽  
Honggang Wei

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