[1]代国威,田志民,樊景超*,等. 面向神经网络结构搜索的植物叶片病害增强识别方法[J].西北林学院学报,2023,38(5):153-161.[doi:10.3969/j.issn.1001-7461.2023.05.21]
　DAI Guo-wei,TIAN Zhi-min,FAN Jing-chao*,et al. Enhanced Identification Method of Plant Leaf Disease Based on Neural Network Structure Search[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2023,38(5):153-161.[doi:10.3969/j.issn.1001-7461.2023.05.21]
点击复制

 面向神经网络结构搜索的植物叶片病害增强识别方法()
分享到：

《西北林学院学报》[ISSN:1001-7461/CN:61-1202/S]

卷:
第38卷
期数:
2023年第5期
页码:
153-161
栏目:
出版日期:
2023-09-30

文章信息/Info

Title:
 Enhanced Identification Method of Plant Leaf Disease Based on Neural Network Structure Search
文章编号:
1001-7461(2023)05-0153-09
作者:
 代国威1; 田志民2; 樊景超1; 3*; 王朝雨4
 (1.中国农业科学院 农业信息研究所/国家农业科学数据中心，北京 100081；2.河北水利电力学院，河北 沧州 061001；3.中国农业科学院 国家南繁研究院，海南 三亚 572025；4.广汉市中医院，四川 广汉 618399)
Author(s):
 DAI Guo-wei1; TIAN Zhi-min2; FAN Jing-chao1; 3*; WANG Chao-yu4
 (1.Agricultural Information Institute,Chinese Academy of Agricultural Sciences,National Agriculture Science Data Center,Beijing 100081,China; 2.Hebei University of Water Resources and Electric Engineering,Cangzhou 061001,Hebei,China; 3.National Nanfan Research Institute (Sanya),Chinese Academy of Agricultural Sciences,Sanya 572025,Hainan,China; 4.Guanghan Hospital of Traditional Medicine,Guanghan 618399,Sichuan,China)
关键词:
 ; 图像处理; 神经网络结构搜索; 模糊c均值聚类; 快速灰度共生矩阵; 叶片病害识别
Keywords:
 ; image processing;  neural network structure search;  fuzzy c-means clustering;  fast grey-level cooccurrence matrix;  leaf disease identification
分类号:
S763.1
DOI:
10.3969/j.issn.1001-7461.2023.05.21
文献标志码:
A
摘要:
 针对植物病害识别模型结构复杂且依赖于人为设计网络结构等问题，通过神经网络结构搜索(NAS)，提出一种基于队列分块的神经网络结构搜索方法(NNSS)，可实现超轻量级高精度植物叶片图像识别模型的自动构建。首先将12种在经济和环境下有益的植物共计22类植物叶片图像作为训练样本，利用模糊c均值聚类(FCM)算法分割植物叶片的感染点，以获得叶片受关注的区域信息；通过图像像素的灰度空间相关性，采用快速灰度共生矩阵(FGLCM)算法提取6类受关注区域的纹理特征信息，获得的特征向量运用主成分变换选择重要特征；提出队列分块的局部搜索空间构造方法，将特征信息通过自动构建的模型进行分类。结果表明，NNSS方法取得了98.33%的准确率，特异性和灵敏性表现最优。相比于AlexNet、GoogLeNet、InceptionV3和VGGNet-16模型，改进VGG-INCEP16模型的性能得到进一步提升，但仍低于NNSS方法，这是由于该方法能结合数据集搜索合适的网络结构，对比次优VGG-INCEP16模型准确率至少提高了2.1%。研究结果显示，NNSS方法能够实现准确识别植物病害，对于神经网络模型结构自动搜索的未来具有较高的实际应用价值。
Abstract:
 Aiming to solve the problems of the complex structure of plant disease recognition models and relying on human-designed network structure,a neural network structure search method based on queueing chunking an NNSS was proposed by neural network architecture search (NAS),which could realize the automatic construction of ultra-lightweight and high-precision plant leaf image recognition models.The method started with a total of 22 classes of plants leaf images of 12 economically and environmentally beneficial plants as training samples and used the fuzzy c-mean clustering (FCM) algorithm to segment the infected points of plant leaves to obtain information on the regions of interest of the leaves.Texture feature information of six classes of regions of interest by the gray-scale spatial correlation of image pixels was extracted by using the fast gray-scale co-generation matrix (FGLCM) algorithm and the important features of the obtained feature vectors were selected by using the principal component transform.A local search space construction method for queue chunking was proposed to classify feature information by an automatically constructed model.The experimental results showed that the NNSS method achieved 98.33% accuracy with the best performance in specificity and sensitivity.Compared with AlexNet,GoogLeNet,InceptionV3,and VGGNet-16 models,the performance of the improved VGG-INCEP16 model was further improved but still lower than the NNSS method due to its ability to search for a suitable network structure in combination with the dataset,which improved the accuracy over the suboptimal VGG-INCEP16 model by at least 2.1%.The NNSS method can accurately identify plant diseases and has a high practical application value for the future automatic search of neural network model structures.

相似文献/References:

[1]多化琼,王喜明*.利用傅立叶变换研究阔叶材纤维细胞排列利用傅立叶变换研究阔叶材纤维细胞排列[J].西北林学院学报,2009,24(02):121.
　DUO Hua qiong,WANG Xi ming*.Analysis of Cell Arrangements in Hardwood by Fourier Transform[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2009,24(5):121.
[2]刘小英,何东健*,张健,等.葡萄干轮廓的图像检测方法研究[J].西北林学院学报,2006,21(05):189.
　LIU Xiaoying{},HE Dongjian*,ZHANG Jian,et al.Image Detecting Method of Raisin's Contour[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2006,21(5):189.
[3]李亚藏,梁彦兰,王庆成. 铅对山梨和山荆子光合作用和叶绿素荧光特性的影响[J].西北林学院学报,2012,27(05):21.
　LI Ya-cang,LIANG Yan-lan,WANG Qing-cheng. Influence of Pb on Photosynthesis and Chlorophyll Fluorescence Characteristics in Pyrus ussuriensis and Malus baccata [J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2012,27(5):21.
[4]张小咏,李佳,杨艳昭,等. 基于SWAT模型的长江源区径流模拟[J].西北林学院学报,2012,27(05):38.
　ZHANG Xiao-yong,LI Jia,YANG Yan-zhao,et al. Runoff Simulation of the Catchment of the Headwaters of the Yangtze River Based on SWAT Model[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2012,27(5):38.
[5]杨红旗,陈广辉,王金林. PVAc改性酚醛树脂制备铝木复合材料研究[J].西北林学院学报,2013,28(01):170.[doi:10.3969/j.issn.1001-7461.2013.01.34]
　YANG Hong-qi,CHEN Guang-hui,WANG Jin-lin. PF Adhesive Modified by PVAc for Manufacturing Technology of Decorative Fiberboard with Aluminum Foils[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2013,28(5):170.[doi:10.3969/j.issn.1001-7461.2013.01.34]
[6]江涛,李秀荣,谢延军,等. 微波预处理对巨尾桉木材渗透性的影响[J].西北林学院学报,2013,28(01):174.[doi:10.3969/j.issn.1001-7461.2013.01.35]
　JIANG Tao,LI Xiu-rong,XIE Yan-jun,et al. Effects of Microwave Pretreatment on the Permeability of Eucalyptus grandis×Eucalyptus urophylla[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2013,28(5):174.[doi:10.3969/j.issn.1001-7461.2013.01.35]
[7]牛晓霆,王逢瑚,曹新民. 明清家具匠师原木下料的工艺原则及措施[J].西北林学院学报,2013,28(01):178.[doi:10.3969/j.issn.1001-7461.2013.01.36]
　NIU Xiao-ting,WANG Feng-hu,CAO Xin-min. Techniques and Principles of Log Cuttings of Furniture Makers in Ming and Qing Dynasties[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2013,28(5):178.[doi:10.3969/j.issn.1001-7461.2013.01.36]
[8]吕金阳,覃卓凯,舒辉,等. 银杉木材构造美学价值[J].西北林学院学报,2013,28(01):183.[doi:10.3969/j.issn.1001-7461.2013.01.37]
　LV Jin-yang,QIN Zhuo-kai,SHU Hui,et al. Esthetical Values in Wood Structure of Cathaya argyrophylla[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2013,28(5):183.[doi:10.3969/j.issn.1001-7461.2013.01.37]
[9]杨艳红,张海敏,孙景荣. 基于传统文化视角的现代家具设计探析[J].西北林学院学报,2013,28(01):188.[doi:10.3969/j.issn.1001-7461.2013.01.38]
　YANG Yan-hong,ZHANG Hai-min,SUN Jing-rong. Study of Modern Furniture Design Based on Traditional Culture[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2013,28(5):188.[doi:10.3969/j.issn.1001-7461.2013.01.38]
[10]黄圣游,叶喜. 新中式家具“中式”传统的界定[J].西北林学院学报,2013,28(01):192.[doi:10.3969/j.issn.1001-7461.2013.01.39]
　HUANG Sheng-You,YE Xi. Definition of Traditional Element in New Chinese Style Furniture[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2013,28(5):192.[doi:10.3969/j.issn.1001-7461.2013.01.39]
[11]多化豫,高峰*,李福胜,等. 基于图像处理的木片与树皮的新识别参数研究[J].西北林学院学报,2015,30(01):207.[doi:doi:10.3969/j.issn.1001-7461.2015.01.34]
　DUO Hua-yu,GAO Feng*,LI Fu-sheng,et al. Approaching to the New Identification Parameter on Wood and Bark Based on Image Processing[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2015,30(5):207.[doi:doi:10.3969/j.issn.1001-7461.2015.01.34]
[12]李应果,杨洁*. 基于阈值分割的单板穿孔缺陷识别算法研究[J].西北林学院学报,2022,37(3):199.[doi:10.3969/j.issn.1001-7461.2022.03.27]
　LI Ying-guo,YANG Jie*. Recognition Algorithm of Single Plate Perforation Defect Based on Threshold Segmentation[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2022,37(5):199.[doi:10.3969/j.issn.1001-7461.2022.03.27]
[13]杨滨,郝景新*,刘拓宇,等. 基于matlab图像处理的CLT木破率测量方法[J].西北林学院学报,2023,38(1):199.[doi:10.3969/j.issn.1001-7461.2023.01.27]
　YANG Bin,HAO Jing-xin*,Liu Tuo-yu,et al. Method of Measuring Wood Failure Percentage Based on Matlab Image Processing[J].JOURNAL OF NORTHWEST FORESTRY UNIVERSITY,2023,38(5):199.[doi:10.3969/j.issn.1001-7461.2023.01.27]

备注/Memo

备注/Memo:
 收稿日期：2022-11-24修回日期：2023-02-06
基金项目：国家重点研发计划项目(2021YFF0704200)；中国农业科学院院级基本科研业务费(Y2022LM20)；中国农业科学院科技创新工程项目(CAAS-ASTIP-2016-AII)。
第一作者：代国威。研究方向：人工智能及农业信息化。E-mail:dgwstyle@foxmail.com
*通信作者：樊景超，博士，副研究员，硕士生导师。研究方向：农业科学数据管理、农业信息技术。E-mail:fanjingchao@caas.cn
更新日期/Last Update: