摘要
苹果树疏花是果园生产管理中的重要环节。准确高效地识别苹果中心花和边花,是研发智能疏花机器人的前提。针对苹果疏花作业中的实际需求,提出了一种基于CRV-YOLO的苹果中心花和边花识别方法。本文基于YOLO v5s模型进行了如下改进:将C-CoTCSP结构融入Backbone,更好地学习上下文信息并提高了模型特征提取能力,提高了模型对外形相似和位置关系不明显的中心花和边花的检测性能。在Backbone中添加改进RFB结构,扩大特征提取感受野并对分支贡献度进行加权,更好地利用了不同尺度特征。采用VariFocal Loss损失函数,提高了模型对遮挡等场景下难识别样本检测能力。在3个品种1837幅图像数据集上进行了实验,结果表明,CRV-YOLO的精确率、召回率和平均精度均值分别为95.6%、92.9%和96.9%,与原模型相比,分别提高3.7、4.3、3.9个百分点,模型受光照变化和苹果品种影响较小。与Faster R-CNN、SSD、YOLOX、YOLO v7模型相比,CRV-YOLO的精确率、平均精度均值、模型内存占用量和复杂度性能最优,召回率接近最优。研究成果可为苹果智能疏花提供技术支持。
Apple tree thinning is an important step in orchard production management.Accurate and efficient recognition of apple king flowers and side flowers is the premise of the development of intelligent flower thinning robot.According to the actual demand of apple flower thinning,a method for recognizing king flowers and side flowers of apple based on CRV-YOLO was proposed.Based on YOLO v5s model,the following improvements were made:firstly,C-CoTCSP structure was integrated into Backbone to better learn contextual information and improve the detection performance of the model for king flowers and side flowers that were similar and the position relationship was not obvious.Then an improved RFB structure was added to the Backbone,with which the receptive field of feature extraction was expanded and the branch contribution degree was weighted to make better use of different scale features.Finally,VariFocal Loss loss function was used to improve the detection ability of the model for samples in occlusion and other scenes.Experiments were conducted on a dataset of 1837 images from three varieties.The results showed that the precision,recall and mAP of the proposed model were 95.6%,92.9%and 96.9%,respectively,which were 3.7 percentage points,4.3 percentage points and 3.9 percentage points higher than those of the original model.The model was less affected by light changes and apple varieties.Compared with that of Faster R-CNN,SSD,YOLOX,and YOLO v7,precision,the mAP and model size and complexity performance of CRV-YOLO were optimal,and recall was close to optimal.The research results can provide technical support for apple intelligent flower thinning.
作者
司永胜
孔德浩
王克俭
刘丽星
杨欣
SI Yongsheng;KONG Dehao;WANG Kejian;LIU Lixing;YANG Xin(College of Information Science and Technology,Hebei Agricultural University,Baoding 071001,China;College of Mechanical and Electrical Engineering,Hebei Agricultural University,Baoding 071001,China)
出处
《农业机械学报》
EI
CAS
CSCD
北大核心
2024年第2期278-286,共9页
Transactions of the Chinese Society for Agricultural Machinery
基金
财政部和农业农村部:国家现代农业产业技术体系项目(CARS-27)。
关键词
苹果花识别
YOLO
v5s
上下文信息
中心花
边花
apple flowers recognition
YOLO v5s
contextual information
king flowers
side flowers
