Underwater Optical Image Interested Object Detection Model Based on Improved SSD

LI Baoqi; HUANG Haining; LIU Jiyuan; LIU Zhengjun; WEI Linzhe

doi:10.11999/JEIT210761

Volume 44 Issue 10

Oct. 2022

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Article Navigation > Journal of Electronics & Information Technology > 2022 > 44(10): 3372-3378

LI Baoqi, HUANG Haining, LIU Jiyuan, LIU Zhengjun, WEI Linzhe. Underwater Optical Image Interested Object Detection Model Based on Improved SSD[J]. Journal of Electronics & Information Technology, 2022, 44(10): 3372-3378. doi: 10.11999/JEIT210761

Citation:

LI Baoqi, HUANG Haining, LIU Jiyuan, LIU Zhengjun, WEI Linzhe. Underwater Optical Image Interested Object Detection Model Based on Improved SSD[J]. Journal of Electronics & Information Technology, 2022, 44(10): 3372-3378. doi: 10.11999/JEIT210761

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Underwater Optical Image Interested Object Detection Model Based on Improved SSD

doi: 10.11999/JEIT210761

1.
Institute of Acoustics, Chinese Academy of Sciences, Beijing 100190, China
2.
Key Laboratory of Science and Technology on Advanced Underwater Acoustic Signal Processing, Chinese Academy of Sciences, Beijing 100190, China

Funds: The National Natural Science Foundation of China (11904386), The Major Projects of the National Basic Scientific Research Plan (JCKY2016206A003), The Youth Innovation Promotion Association of Chinese Academy of Sciences (2019023)

Received Date: 2021-07-30
Accepted Date: 2021-11-18
Rev Recd Date: 2021-11-15

Available Online: 2021-11-19

Publish Date: 2022-10-19

Abstract

Abstract

In order to solve the problem of low detection accuracy of SSD-MV2, a Selective and Efficient Block (SEB) and a Selective and Deformable Block (SDB) are proposed. At the same time, the basic network and additional feature extraction network of SSD-MV2 are redesigned by using SEB and SDB, which is named SSD-MV2SDB, and a set of reasonable expansion coefficient of basic network and number of SDB in additional feature extraction network are selected for SSD-MV2SDB. On UOI-DET, mAP of SSD-MV2SDB is 3.04% higher than that of SSD-MV2. The experimental results show that SSD-MV2SDB is suitable for underwater optical image interested object detection task.
- Underwater optical image interested object detection,
- Single Shot Detection (SSD),
- MobileNet V2,
- Deformable convolution,
- Channel selectable

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References(19)

References

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