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Volume 43 Issue 10
Oct.  2021
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Baoqi LI, Haining HUANG, Jiyuan LIU, Zhengjun LIU, Linzhe WEI. Synthetic Aperture Sonar Underwater Multi-scale Target Efficient Detection Model Based on Improved Single Shot Detector[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2854-2862. doi: 10.11999/JEIT201042
Citation: Baoqi LI, Haining HUANG, Jiyuan LIU, Zhengjun LIU, Linzhe WEI. Synthetic Aperture Sonar Underwater Multi-scale Target Efficient Detection Model Based on Improved Single Shot Detector[J]. Journal of Electronics & Information Technology, 2021, 43(10): 2854-2862. doi: 10.11999/JEIT201042

Synthetic Aperture Sonar Underwater Multi-scale Target Efficient Detection Model Based on Improved Single Shot Detector

doi: 10.11999/JEIT201042
Funds:  The National Natural Science Foundation of China(11904386), The State Administration of Science, Technology and Industry Program (JCKY2016206A003), The Youth Innovation Promotion Association of Chinese Academy of Sciences (2019023)
  • Received Date: 2020-12-14
  • Rev Recd Date: 2021-05-29
  • Available Online: 2021-08-27
  • Publish Date: 2021-10-18
  • In view of the problem that the efficient detection model SSD-MV2 (Single Shot Detector MobileNet V2) has low detection accuracy to underwater multi-scale targets in Synthetic Aperture Sonar (SAS) images, a novel feature extraction module Extended Selective Kernel (ESK) is proposed in this paper. ESK has the advantages of channel scalability, channel selection and few model parameters. At the same time, the basic network and additional feature extraction network of SSD are redesigned by using ESK module, which is named SSD-MV2ESK, and a set of reasonable expansion coefficient and multi-scale coefficient are selected for SSD-MV2ESK. On SST-DET, the mAP of SSD-MV2ESK is 4.71% higher than that of SSD-MV2 when the model parameters are basically the same. The experimental results show that SSD-MV2ESK is suitable for SAR underwater multi-scale target detection task in embedded platform.
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