The ship classification and detection method of optical remote sensing image based on improved YOLOv7-tiny

Jinwei Cheng; Jie Yuan; Xiaoning Hu; Baorong Xie; Junrui Wang

doi:10.1117/12.3014371

9 January 2024 The ship classification and detection method of optical remote sensing image based on improved YOLOv7-tiny

Jinwei Cheng, Jie Yuan, Xiaoning Hu, Baorong Xie, Junrui Wang

Author Affiliations +

Proceedings Volume 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023); 129691F (2024) https://doi.org/10.1117/12.3014371
Event: International Conference on Algorithm, Imaging Processing and Machine Vision (AIPMV 2023), 2023, Qingdao, China

Abstract

In view of the fault and leak detection problems caused by complex scenes of offshore area in remote sensing image ship detection, a lightweight ship classification detection method is proposed based on improved YOLOv7-tiny. On the one hand, this method stacks a lightweight feature extraction module and applies it to the backbone feature extraction network, which significantly reduces the parameter and computational complexity and does not weaken the network's ability of feature extraction. On the other hand, this method introduces spatial information into the feature pyramid, raising the discrimination of features at different scales, to improve the classification and detection ability of the network. This method has been tested on the remote sensing image ship data set. The experimental results show that the average accuracy of ship classification detection based on the improved network is increased by 2.9%. Meanwhile, the parameter quantity and computational complexity are better than YOLOv7-tiny, with a 15% reduction in parameter quantity and a 24% reduction in computational complexity.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Jinwei Cheng, Jie Yuan, Xiaoning Hu, Baorong Xie, and Junrui Wang "The ship classification and detection method of optical remote sensing image based on improved YOLOv7-tiny", Proc. SPIE 12969, International Conference on Algorithm, Imaging Processing, and Machine Vision (AIPMV 2023), 129691F (9 January 2024); https://doi.org/10.1117/12.3014371

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