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YOLOv7-ship: An Efficient Method for Marine Ship Detection Based on Wave Glider

Published: 28 February 2024 Publication History

Abstract

Ship detection based on wave gliders plays an important role in tasks such as maritime patrols, target tracking, and maritime traffic control. However, the complex and diverse sea environment, as well as the large differences in the appearance and scale of ships on the sea, have led to traditional detection algorithms experiencing issues such as false detection, missed detection of small targets, and incomplete detection of ship mast areas in ship detection tasks. To alleviate this dilemma, we designed a ship detector named YOLOv7-ship based on YOLOv7-tiny. Firstly, we introduce a parameter-free attention module (SimAM) in the backbone network to search for attention regions in the scene, thereby helping to solve the problem of false detection under complex marine environment interference. Secondly, we designed a mixed upsampling feature fusion method and specifically added a small target detection layer to enhance the detection of small targets. Finally, we introduce Wise-IOU into the loss function, and carry out different gradient gain allocation strategies in stages to solve the problem of incomplete detection of ship mast. The experimental results show that the YOLOv7-ship detector we designed achieves [email protected] 99.4% and 81.1% on the public dataset SeaShips and our wave glider dataset WG-Ships, respectively, while maintaining real-time inference speed and outperforming most mainstream models in performance.

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Weina Zhou and Lu Liu. [n. d.]. Real time detection method for multi-scale ships in complex scenes(in Chinese). Telecommunications Science 38, 10 ([n. d.]), 67–78.

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cover image ACM Other conferences
ICCPR '23: Proceedings of the 2023 12th International Conference on Computing and Pattern Recognition
October 2023
589 pages
ISBN:9798400707988
DOI:10.1145/3633637
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Published: 28 February 2024

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  1. YOLOv7-tiny
  2. attention module
  3. ship detection
  4. wave glider

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