Detection of microalgae objects based on the Improved YOLOv3 model.
Detection of microalgae objects based on the Improved YOLOv3 model.
复制标题
基于改进的YOLOv3模型的微藻物体检测。
DOI：
10.1039/d1em00159k
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发表时间：
2021-09
期刊：
影响因子：
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通讯作者：
Wang Yuezhu
中科院分区：
文献类型：
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作者：
Cao Mengying;Wang Junsheng;Chen Yantong;Wang Yuezhu
微藻在以压载水为载体的外来生物入侵中起着主要作用，传统的压载水检测方法在识别微藻种类上存在诸多局限性。因此，本文提出了一种基于改进YOLOv 3模型的压载水微藻识别方法。该方法首先使用轻量级网络MobileNet代替原来YOLOv 3模型中的Darknet-53网络作为特征提取的骨干网络。其次，引入改进的空间金字塔池化（SPP）来池化和连接多尺度区域特征，以减少检测小物体时的位置误差。然后，综合考虑包围盒的重叠面积、中心点距离和长宽比，采用完全IoU（CIoU）算法对YOLOv 3模型的损失函数进行优化。最后，该方法与其他最新的方法在建立的数据集上进行了实验比较。实验结果表明，在相同条件下，改进后的YOLOv 3模型平均准确率达到98.90%，检测效率比原YOLOv 3模型提高8.59%，优于现有方法。该方法识别单张图像的平均时间为0.086 s，对微藻种类的识别具有较好的检测效果。
Microalgae play a major role in the invasion of alien organisms with ballast water as a carrier, and traditional ballast water detection methods have many limitations in identifying microalgae species. Therefore, this paper proposes a method to identify microalgae in ballast water based on an Improved YOLOv3 model. The method first used a lightweight network MobileNet instead of the Darknet-53 network as the backbone network of feature extraction in the original YOLOv3 model. Secondly, improved spatial pyramid pooling (SPP) is introduced to pool and concatenate the multi-scale regional features so as to reduce the position error when detecting small objects. Then, by considering the overlap area of the bounding box, central point distance and aspect ratio, the Complete IoU (CIoU) algorithm is used to optimize the loss function of the YOLOv3 model. Finally, the proposed method is experimentally compared with other latest methods on the established dataset. The experimental results demonstrated that under the same conditions, this Improved YOLOv3 model achieves an average accuracy of 98.90%, and the detection efficiency is 8.59% higher than that of the original YOLOv3 model and is better than the existing methods. The average time of this method to identify a single image is 0.086 s, and it has a good detection effect on the identification of microalgae species.