北京林业大学学报2018，Vol.40Issue(12)：132-137,6.DOI:10.13332/j.1000-1522.20180182
基于双路卷积神经网络的植物叶片识别模型
Plant leaf recognition model based on two-way convolutional neural network
摘要
Abstract
[Objective] Aiming at the problem that the leaf edge shape has an excessive effect on the convolution layer during the process of identifying the leaf of convolutional neural network, which leads to the error recognition of similar edge shape leaves, a plant leaf recognition model of two-way convolutional neural network was proposed. [Method] The model considers the edge shape and internal texture features of the blade information to construct a two-way convolutional neural network structure. Wherein, the shape feature path used a network structure of 7 layers of convolution layers, the first three layers used large-size 11 × 11 and 5 × 5 convolution kernels, extracting large field of view features to complete blade shape feature extraction, the other 4 layers of convolution layer used a 3 × 3 small size convolution core, extracting blade detail features. The two types of feature linear transformations were merged into one-dimensional feature vectors through a fully connected layer. Finally, the fully connected layer identified the plant leaf species. [Result] The experimental results showed that the two-wayconvolutional network model was compared with the single-channel convolutional network and the image recognition classification recognition model. On the Flavia leaf dataset and the expanded complex background leaf dataset, the accuracy of Top-1 recognition increased to 99. 28％ and 97. 31％, respectively. The accuracy of Top-3 recognition increased to 99. 97％ and 99. 74％, respectively. The standard deviation decreased to 0. 18 and 0. 20 compared with other identification and classification models. [Conclusion] The blade recognition and classification model proposed in this paper can effectively avoid the problems caused by the similar blade edge shape interference and improve the recognition accuracy of leaf plant species.关键词
植物识别/叶片图像/特征融合/卷积神经网络Key words
plant identification/blade image/feature fusion/convolutional neural network分类
农业科技引用本文复制引用
于慧伶,麻峻玮,张怡卓..基于双路卷积神经网络的植物叶片识别模型[J].北京林业大学学报,2018,40(12):132-137,6.基金项目
林业公益性行业科研专项(201504307) （201504307）
中央高校基本科研业务费项目(2572017CB34) （2572017CB34）
