基于改进YOLO V5s模型的遥感图像目标检测及应用  

Application of Improved YOLO V5s Model for Regional Poverty Assessment using Remote Sensing Image Target Detection

作　　者：张晨光 滕桂法[1] 丁文卿 ZHANG Chen-guang;TENG Gui-fa;DING Wen-qing(College of Information Science and Technology,Agricultural University of Hebei,Baoding Hebei 071000,China;School of Computer and Information Technology,Cangzhou Jiaotong College,Cangzhou Hebei 061100,China;Bohai College,Agricultural University of Hebei,Cangzhou Hebei 061100,China)

机构地区：[1]河北农业大学信息科学与技术学院,河北保定071000 [2]沧州交通学院计算机与信息技术学院,河北沧州061100 [3]河北农业大学渤海校区,河北沧州061100

出　　处：《计算机仿真》2024年第6期244-254,共11页Computer Simulation

基　　金：沧州市科技局基于大数据推荐算法及遥感的市域经济发展研究规划(213102003);河北省省属高等学校基本科研业务费研究项目(KY2021052);河北省人力资源和社会保障厅面向就业市场的新工科建设中应用型大数据人才培养研究(JRSHZ-2022-02037)。

摘　　要：利用改进YOLO V5s模型实现遥感图像目标检测并用于地域贫困评估。针对现有模型提出了三点改进:加强PAN结构、基于bounding box的RIOU_Loss回归损失函数、协同注意力机制。同时将遥感图像目标作为表征,计算连续时间节点内的贫困率变化。实验结果表明,改进模型的P、R、mAP@0.5、mAP@0.5:0.95值存在不同程度的提升,而Loss值有所下降。因此,与原模型相比,改进模型具备更精准的目标检测能力。同时,与传统的统计数据方法相比,改进模型为地域贫困评估提供了一种等效的无数据评估思路。This study aims at applying the improved YOLO V5s model for the assessment of regional poverty using remote sensing image target detection.For this purpose,three improvements were made to the model.So,a new enhanced PAN structure was proposed.Accordingly,a new RIOU_Loss regression loss function of bounding box was proposed.Furthermore,a new collaborative attention mechanism was put forward.In addition,while objects in the remote sensing images were used as the representations of poverty status,the changes in the images were considered to evaluate the regional poverty rate in a continuous time interval.The results show that the values of P,R,mAP@0.5 and mAP@0.5:0.95 of the model are improved,while the Loss value is decreased.Therefore,compared with the original model,the improved model has more accurate object detection capabilities.Meanwhile,compared with traditional statistical data methods,the improved model provides an equivalent dataless evaluation approach for regional poverty assessment.

关 键 词：遥感 目标检测 仿真 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]