Smart Agriculture ›› 2019, Vol. 1 ›› Issue (4): 42-49.doi: 10.12133/j.smartag.2019.1.4.201908-SA002
• Information Perception and Acquisition • Previous Articles Next Articles
Wu Huarui1,2
Received:
2019-08-14
Revised:
2019-11-07
Online:
2019-10-30
Published:
2019-12-24
CLC Number:
Wu Huarui. Method of tomato leaf diseases recognition method based on deep residual network[J]. Smart Agriculture, 2019, 1(4): 42-49.
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URL: http://www.smartag.net.cn/EN/10.12133/j.smartag.2019.1.4.201908-SA002
1 | Park H , JeeSook E , Kim S H . Crops disease diagnosing using image-based deep learning mechanism[C]// IEEE 2018 International Conference on Computing and Network Communications, 2018: 23-26. |
2 | Ermayanti A , Nidia Enjelita S , Nuraini S , et al . Dempster-Shafer method for diagnose diseases on vegetable[C]// 2018 6th International Conference on Cyber and IT Service Management (CITSM), 2018. |
3 | Schor N , Bechar A , Ignat T , et al . Robotic disease detection in greenhouses: combined detection of powdery mildew and tomato spotted wilt virus[J]. IEEE Robotics and Automation Letters, 2016, 1(1): 354-360. |
4 | 张云龙, 袁浩, 张晴晴, 等 . 基于颜色特征和差直方图的苹果叶部病害识别方法[J]. 江苏农业科学, 2017, 45(14): 171-174. |
5 | 夏永泉, 王兵, 支俊, 等 . 基于随机森林方法的小麦叶片病害识别研究[J]. 图学学报, 2018, 39(1): 57-62. |
Xia Y , Wang B , Zhi J , et al . Identification of wheat leaf disease based on random forest method[J]. Journal of Graphics, 2018, 39(1): 57-62. | |
6 | Castelao Tetila E , Brandoli Machado B , Belete N A D S , et al . Identification of soybean foliar diseases using unmanned aerial vehicle images[J]. IEEE Geoscience and Remote Sensing Letters, 2017, 14(12): 2190-2194. |
7 | 魏丽冉, 岳峻, 李振波, 等 . 基于核函数支持向量机的植物叶部病害多分类检测方法[J]. 农业机械学报, 2017, 48(S1): 166-171. |
Wei L , Yue J , Li Z , et al . Multi-classification detection method of plant leaf disease based on kernel function SVM[J]. Transactions of the CSAM, 2017, 48(S1): 166-171. | |
8 | 芦兵, 孙俊, 毛罕平, 等 . 高光谱和图像特征相融合的生菜病害识别[J]. 江苏农业学报, 2018, 34(6): 1254-1259. |
Lu B , Sun J , Mao H , et al . Disease recognition of lettuce with feature fusion based on hyperspectrum and image[J]. Jiangsu Journal of Agricultural Sciences, 2018, 34(6): 1254-1259. | |
9 | 胡维炜, 张武, 刘连忠 . 基于Variance-SFFS的小麦叶部病害图像识别[J]. 湖南农业大学学报(自然科学版), 2018, 44(02): 225-228. |
Hu W , Zhang W , Liu L . Identification of wheat leaf diseases based on Variance-SFFS algorithm[J]. Journal of Hunan Agricultural University(Natural Sciences), 2018, 44(02): 225-228. | |
10 | 张芳, 李晓辉, 杨洪伟 . 复杂背景下植物叶片病害的图像特征提取与识别技术研究[J]. 辽宁大学学报(自然科学版), 2016, 43(04): 311-318. |
Zhang F , Li X , Yang H . Image feature extraction and recognition of plant leaf disease in complex background[J]. Journal of Liaoning University (Natural Sciences), 2016, 43(04): 311-318. | |
11 | Kaur S , Pandey S , Goel S . Semi-automatic leaf disease detection and classification system for soybean culture[J]. IET Image Processing, 2018, 12(6): 1038-1048. |
12 | Zhang X , Qiao Y , Meng F , et al . Identification of maize leaf diseases using improved deep convolutional neural networks[J]. IEEE Access, 2018, 6: 30370-30377. |
13 | 宋丽娟 . 基于区分深度置信网络的病害图像识别模型[J]. 计算机工程与应用, 2017, 53(21): 32-36, 48. |
Song L . Recognition model of disease image based on discriminative deep belief networks[J]. Computer Engineering and Applications, 2017, 53(21): 32-36, 48. | |
14 | 王艳玲, 张宏立, 刘庆飞, 等 . 基于迁移学习的番茄叶片病害图像分类[J]. 中国农业大学学报, 2019, 24(6): 124-130. |
Wang Y , Zhang H , Liu Q , et al . Image classification of tomato leaf diseases based on transfer learning[J]. Journal of China Agricultural University, 2019, 24(6): 124-130. | |
15 | Khadabadi G C , Kumar A , Rajpurohit V S . Identification and classification of diseases in carrot vegetable using discrete wavelet transform[C]// International Conference on Emerging Research in Electronics. IEEE, 2016. |
16 | Siddharth Singh Chouhan, KaulAjay, Uday Pratap Singh, et al . Bacterial foraging optimization based radial basis function neural network (BRBFNN) for identification and classification of plant leaf diseases: An automatic approach towards plant pathology[J]. IEEE Access, 2018, 6: 8852-8863. |
17 | 陈桂芬, 赵姗, 曹丽英, 等 . 基于迁移学习与卷积神经网络的玉米植株病害识别[J]. 智慧农业, 2019, 1(2): 34-44. |
Chen G , Zhao S , Cao L , et al . Corn plant disease recognition based on migration learning and convolutional neural network[J]. Smart Agriculture, 2019, 1(2): 34-44. | |
18 | 张航, 程清, 武英洁, 等 . 一种基于卷积神经网络的小麦病害识别方法[J]. 山东农业科学, 2018, 50(3): 137-141. |
Zhang H , Cheng Q , Wu Y , et al . A method of wheat disease identification based on convolutional neural network[J]. Shandong Agricultural Sciences, 2018, 50(3): 137-141. | |
19 | 贾建楠, 吉海彦 . 基于病斑形状和神经网络的黄瓜病害识别[J]. 农业工程学报, 2013, 29(25): 115-121. |
Jia J , Ji H . Recognition for cucumber disease based on leaf spot shape and neural network[J]. Transactions of the CSAE, 2013, 29(25): 115-121. | |
20 | Francis J , Anto S D D , Anoop B K . Identification of leaf diseases in pepper plants using soft computing techniques[C]// 2016 Conference on Emerging Devices and Smart Systems. IEEE, 2016. |
21 | Krizhevsky A , Sutskever I , Hinton G . ImageNet classification with deep convolutional neural networks[C]// NIPS. Curran Associates Inc. 2012. |
22 | He K , Sun J . Convolutional neural networks at constrained time cost[C]// 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). 2015. |
23 | Szegedy C , Liu W , Jia Y , et al . Going deeper with convolutions[C]// 2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2015. |
24 | He K , Zhang X , Ren S , et al . Deep residual learning for image recognition[C]// 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2016. |
25 | Wu S , Zhong S H , Liu Y . Steganalysis via deep residual network[C]// 2016 IEEE 22nd International Conference on Parallel and Distributed Systems (ICPADS), IEEE, 2016. |
26 | 厍向阳, 韩伊娜 . 基于残差网络的小型车辆目标检测算法[J]. 计算机应用研究, 37(8):1-6. |
She X , Han Y . Small vehicle target detection algorithm based on residual network[J]. Application Research of Computers, 2019, 37(8): 1-6. | |
27 | 郭玥秀, 杨伟, 刘琦, 等 . 残差网络研究综述[J]. 计算机应用研究, [2019-11-08]. |
Guo Y , Yang W , Liu Q , et al . Survey of residual network[J]. Application Research of Computers, [2019-11-08]. | |
28 | Reagen B , Hernandez-Lobato J M , Adolf R , et al . A case for efficient accelerator design space exploration via Bayesian optimization[C]// 2017 IEEE/ACM International Symposium on Low Power Electronics and Design. ACM, 2017. |
29 | 崔佳旭, 杨博 . 贝叶斯优化方法和应用综述[J]. 软件学报, 2018, 29(10): 3068-3090. |
Cui J , Yang B . Survey on Bayesian optimization Methodology and Applications[J]. Journal of Software, 2018, 29(10): 3068-3090. |
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