基于注意力机制金字塔网络的麦穗检测方法  

Wheat Spikes Detection Method Based on Pyramidal Network of Attention Mechanism

作　　者：章权兵[1] 胡姗姗[1] 舒文灿 程鸿[1] ZHANG Quanbing;HU Shanshan;SHU Wencan;CHENG Hong(National Engineering Research Center for Agro-Ecological Big Data Analysis and Application, Anhui University, Hefei 230601, China)

机构地区：[1]安徽大学农业生态大数据分析与应用技术国家地方联合工程研究中心,合肥230601

出　　处：《农业机械学报》2021年第11期253-262,共10页Transactions of the Chinese Society for Agricultural Machinery

基　　金：国家自然科学基金项目(61605002);安徽省自然科学基金项目(2008085MF209);安徽省高等学校自然科学研究项目(KJ2019ZD04、KJ2020ZD02)。

摘　　要：为了准确预测小麦产量,提出了一种基于特征金字塔网络改进的小麦穗部检测方法。针对检测结果中存在的误检或漏检等问题,本文首先在原始特征提取网络的编码和解码区域分别引入通道注意力机制和空间注意力机制,以增加对麦穗空间信息和语义信息的提取,有效提升网络对遮挡麦穗的检测性能;其次对原始区域建议网络的输入进行改进,设计了一种加权区域建议网络,在通道级别上将高层具有强语义信息的低分辨率特征图融合在一起,经过一系列的全连接层和激活函数生成对应维度的概率后,对底层高分辨率特征图进行加权以增强有用的信息通道,为难以检测的较小麦穗生成更精确的检测框。关于实地采集的灌浆期麦穗图像的实验结果表明,本文方法明显改善了对遮挡麦穗和较小麦穗的检测效果,其检测精确度、召回率和平均精度分别达到80.53%、87.12%和88.53%。通过对公开ACID数据集上不同时期麦穗检测结果的对比分析,进一步验证了本文方法的有效性。With the aim to predict the wheat yield accurately,an improved wheat spikes detection method based on feature pyramid network was proposed.In order to solve the problem of misdiagnosis or omission in the detection results,channel attention mechanism and spatial attention mechanism were introduced into the coding and decoding regions of the original feature extraction network,which increased the extraction of spatial information and semantic information on the wheat spikes and effectively improved the detection performance of the network for obscured wheat spikes.At the same time,a weighted-region proposal network was designed to improve the input of the original region proposal network,in which several low-resolution feature maps with strong semantic information characteristics were fused together on channel levels.After a series of full connection layers and activation functions,the fused feature map was converted to probability of the corresponding channels,which were used to weight the underlying high-resolution feature maps to enhance useful information channels.Thus,a more accurately detection frame was generated for smaller spikes which were difficult to detect.The experimental results of the collected wheat spikes images showed that the method could significantly improve the detection effect of the shaded and smaller wheat spikes,where the precision of recognition,recall rate and average precision were 80.53%,87.12%and 88.53%,respectively.Through the comparative analysis of wheat spikes detection results in different periods on the public ACID data set,the validity of the proposed method was further verified.

关 键 词：麦穗检测 金字塔网络 特征提取 注意力机制 加权区域建议网络 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]