沈阳化工大学学报 ›› 2024, Vol. 38 ›› Issue (2): 167-172.doi: 10.3969/j.issn.2095-2198.2024.02.012
基于YOLOV3改进的算法在对地目标检测中的应用
1.沈阳化工大学 信息工程学院, 辽宁 沈阳 110142；2.中国科学院 沈阳自动化研究所光电信息技术研究室, 辽宁 沈阳 110169
Application of Improved YOLOV3 Algorithm in Ground Object Detection
1. Shenyang University of Chemical Technology， Shenyang 110142， China； 2. Shenyang Institute of Automation, Chinese Academy of Sciences， Shenyang 110169， China
摘要：
对地目标检测因其视野旷阔，在交通安全、无人机侦察等领域应用广泛.对地目标具有数量多、尺度小的特点，导致检测精度不高、召回率低.针对上述问题，提出了一种基于YOLOV3改进的对地目标检测算法.首先，对数据集进行维度聚类，设计新的锚框尺寸，将先验数据融入模型，增强检测模型的有效性；其次，改进原有的网络模型，优化YOLOV3的目标预测框损失函数，使用CIoU损失代替原有的和方差损失，提高了目标预测框的回归稳定性.实验结果表明：改进的算法在VisDrone2018数据集上相对YOLOV3算法的召回率提高了11.2%，平均准确率均值提高了3.36%，改进的算法对对地目标检测的结果优于原本的YOLOV3算法.
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