一种用于低分辨率小目标的水下垃圾检测算法
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郑州轻工业大学

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TP391.4

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河南省科技攻关项目(222102210015);青年科学家项目(225200810098)


An underwater trash detection algorithm for low-resolution small targets
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Zhengzhou University of Light Industry

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    摘要:

    水下垃圾检测是水下机器人处理水下垃圾的关键技术。然而,水下环境的复杂多变和光照条件的不佳,以及传统CNN模型中步长卷积导致的细节信息丢失和低分辨率图像表现不佳等问题,限制了现有模型的准确度和速度。为了解决这些问题,本文提出了一种新型的水下垃圾检测算法SPDC-YOLOv8。该算法在YOLOv8的主干网络中采用了基于自适应空间分解的CNN模块SPD-Conv,替换了步长卷积,从而提高了模型对低分辨率图像和小物体检测的精确性。同时,在模型的上采样过程中使用了CARAFE算子,增强了水下垃圾的语义信息和特征表达能力,进而提高了目标检测的鲁棒性。实验结果显示,本文提出的方法在trash_ICRA19数据集和TrashCan数据集上分别获得了98.6%和91.2% 的准确率,相比原始YOLOv8模型分别提高了0.3%和0.8%,计算时间均为2.6ms。本文所提出的改进后的YOLOv8算法更适应水下复杂环境的检测任务。

    Abstract:

    Underwater trash detection is a key technology for underwater robots to handle underwater trash. However, the complexity and variability of the underwater environment and poor lighting conditions, as well as the loss of detail information and poor performance of low-resolution images due to step-length convolution in traditional CNN models, limit the accuracy and speed of existing models. In order to solve these problems, this paper proposes a novel underwater rubbish detection algorithm SPDC-YOLOv8. The algorithm employs an adaptive spatial decomposition-based CNN module SPD-Conv in the backbone network of YOLOv8, replacing the step-length convolution, thus improving the accuracy of the model for low-resolution images and small object detection. Meanwhile, the CARAFE operator is used in the up-sampling process of the model, which enhances the semantic information and feature representation of underwater rubbish, and thus improves the robustness of Object Detection. The experimental results show that the method proposed in this paper obtains 98.6% and 91.2% accuracy on the trash_ICRA19 dataset and TrashCan dataset, respectively, and improves 0.3% and 0.8% compared with the original YOLOv8 model, and the computation time is 2.6 ms in both cases. The improved YOLOv8 algorithm proposed in this paper is more adapted to the underwater complex environment underwater environment.

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韩丽,马春海,林志浩,等. 一种用于低分辨率小目标的水下垃圾检测算法[J]. 科学技术与工程, , ():

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  • 收稿日期:2023-11-03
  • 最后修改日期:2024-05-17
  • 录用日期:2024-05-21
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