[1] 毛文华, 郑永军, 张银桥, 苑严伟, 张小超. 基于机器视觉的草地蝗虫识别方法. 农业工程学报, 2008, 24(11): 155-158.
MAO W H, ZHENG Y J, ZHANG Y J, YUAN Y W, ZHANG X C. Grasshopper detection method based on machine vision. Transactions of the Chinese Society of Agricultural Engineering, 2008, 24(11): 155-158. (in Chinese)
[2] 宋凯. 基于计算机视觉的农作物病害识别方法的研究[D]. 沈阳: 沈阳农业大学, 2008.
SONG K. Study of recognition method of crop disease based on computer vision[D]. Shenyang: Shenyang Agricultural University, 2008. (in Chinese)
[3] 陈建能, 张国凤. 计算机视觉技术在农业中的应用及展望. 甘肃农大学报, 2003, 38(2): 248-253.
CHEN J N, ZHANG G F. Application and prospect of computer vision technique in agriculture. Journal of Gansu Agricultural University, 2003, 38(2): 248-253. (in Chinese)
[4] 韩瑞珍, 何勇. 基于计算机视觉的大田害虫远程自动识别系统. 农业工程学报, 2013, 29(3): 156-162.
HAN R Z, HE Y. Remote automatic identification system of field pests based on computer vision. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(3): 156-162. (in Chinese)
[5] 刘国成, 张杨, 黄建华, 汤文亮. 基于K-means聚类算法的叶螨图像分割与识别. 昆虫学报, 2015, 58(12):1338-1343.
LIU G C, ZHANG Y, HUANG J H, TANG W L. A method for segmentation and recognition of spider mites based on K-means clustering algorithm. Acta Entomologica Sinica, 2015, 58(12): 1338-1343. (in Chinese)
[6] YAAKOB S N, JAIN L. An insect classification analysis based on shape features using quality threshold ARTMAP and moment invariant. Applied Intelligence, 2012, 37(1): 12-30.
[7] 姚青, 吕军, 杨保军, 薛杰, 郑宏海. 基于图像的昆虫自动识别与计数研究进展. 中国农业科学, 2011, 44(14): 2886-2899.
YAO Q, LÜ J, YANG B J, XUE J, ZHENG H H. Progress in research on digital image processing technology for automatic insects identification and counting. Scientia Agricultura Sinica, 2011, 44(14): 2886-2899. (in Chinese)
[8] DING W, TAYLOR G. Automatic moth detection from trap images for pest management. Computers & Electronics in Agriculture, 2016, 123: 17-28.
[9] LIU Z, YANG G, ZHANG H, HE Y. Localization and classification of paddy field pests using a saliency map and deep convolutional neural network. Scientific Reports, 2016, 6: 20410.
[10] 马晓, 张番栋, 封举富. 基于深度学习特征的稀疏表示的人脸识别方法. 智能系统学报, 2016, 11(3): 279-286.
MAO X, ZHANG F D, FENG J F. Sparse representation via deep learning features based face recognition method. CAAI Transactions on Intelligent Systems, 2016, 11(3): 279-286. (in Chinese)
[11] WEN Y, XIANG Y, FU Y. A joint classification approach via sparse representation for face recognition//Proceedings of the 12th International Conference on Signal Processing of the Ieee, 2015: 1387-1391.
[12] MOURAO A, BORGES P, CORREIA N, MAGALHAES J. Sparse reconstruction of facial expressions with localized gabor moments// Proceedings of the 22nd European Signal Processing Conference (EUSIPCO), 2014: 1642-1646.
[13] THAVALENGAL S, MANDAL S, SAO A K. Significance of dictionary for sparse coding based pose invariant face recognition// 2014 20th National Conference on Communications (NCC), 2014: 1-5.
[14] 詹曙, 王俊, 杨福猛, 方琪. 基于Gabor特征和字典学习的高斯混合稀疏表示图像识别. 电子学报, 2015, 43(3): 523-528.
ZHAN S, WANG J, YANG F M, FANG Q. Gaussian mixture sparse representation for image recognition based on Gabor features and dictionary learning. Acta Electronica Sinica, 2015, 43(3): 523-528. (in Chinese)
[15] 周昊, 火元莲. 基于LBP算子和稀疏表达分类器的人脸表情识别. 自动化与仪器仪表, 2014(10): 137-139.
ZHOU H, HUO Y L. Facial expression recognition based on LBP operator and sparse expression classifier. Automation and instrumentation 2014(10): 137-139. (in Chinese) ,
[16] 龚永罡. 基于局部HOG特征的稀疏表达车牌识别算法. 计算机仿真, 2011, 28(4): 367-369.
GONG Y G. License plate recognition algorithm with sparse representation based on local HOG. Computer Simulation, 2011, 28(4): 367-369. (in Chinese)
[17] WRIGHT J, YANG A, GANESH A, SASTRY S S, MA Y. Robust face recognition via sparse representation. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2008, 31(2): 210-227.
[18] 韩安太, 郭小华, 廖忠, 陈志强, 韩建国. 基于压缩感知理论的农业害虫分类方法. 农业工程学报, 2011, 27(6): 203-207.
HAN A T, GUO X H, LIAO Z, CHEN Z Q, HAN J G. Classification of agricultural pests based on compressed sensing theory. Transactions of the Chinese Society of Agricultural Engineering, 2011, 27(6): 203-207. (in Chinese)
[19] 张超凡, 王儒敬, 谢成军. 基于多特征字典学习的害虫图像自动分类方法. 计算机应用与软件, 2017, 34(3): 142-147.
ZHANG C F, WANG R J, XIE C J. Automatic classification method for pest image based on multi-feature dictionary learning. Computer Applications and Software, 2017, 34(3): 142-147. (in Chinese)
[20] 胡永强, 宋良图, 张洁, 谢成军, 李瑞. 基于稀疏表示的多特征融合害虫图像识别. 模式识别与人工智能, 2014, 27(11): 985-992.
HU Y Q, SONG L T, ZHANG J, XIE C J, LI R. Pest image recognition of multi-feature fusion based on sparse representation. Pattern Recognition and Artificial Intelligence, 2014, 27(11): 985-992. (in Chinese)
[21] XIE C, ZHANG J, LI R, HONG P. Automatic classification for field crop insects via multiple-task sparse representation and multiple- kernel learning. Computers & Electronics in Agriculture, 2015, 119(1): 123-132.
[22] 谢成军, 李瑞, 董伟, 宋良图, 张洁. 基于稀疏编码金字塔模型的农田害虫图像识别. 农业工程学报, 2016, 32(17): 144-151.
XIE C J, LI R, DONG W, SONG L T, ZHANG J. Recognition for insects via spatial pyramid model using sparse coding. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(17): 144-151. (in Chinese)
[23] LYTLE D A, MARTINEZ-MU O G, ZHANG W, LARIOS N, SHAPIRO L. Automated processing and identification of benthic invertebrate samples. Journal of the North American Benthological Society, 2010, 29(3): 867-874.
[24] 冼鼎翔, 姚青, 杨保军, 罗举, 谭畅. 基于图像的水稻灯诱害虫自动识别技术的研究. 中国水稻科学, 2015, 29(3): 299-304.
XIAN D X, YAO Q, YANG B J, LUO J, TAN C. Automatic identification of rice light-trapped pests based on images. Chinese Journal of Rice Science, 2015, 29(3): 299-304. (in Chinese)
[25] 赵娟. 基于Gabor小波与支持向量机对储粮害虫分类识别. 计算机与现代化, 2008(4): 67-69.
ZHAO J. Recognition for pests in stored-grain based on Gabor wavelet and SVM. Computer and Modernization, 2008(4): 67-69. (in Chinese)
[26] YAO Q, CHEN G T, WANG Z. Automated detection and identification of white-backed planthoppers in paddy fields using image processing. Journal of Integrative Agriculture, 2017, 16(7): 1547-1557.
[27] PERONA P, MALIK J. Scale-space and edge detection using anisotropic diffusion. Ieee Transactions on Pattern Analysis and Machine Intelligence, 1990, 12(7): 629-639.
[28] 刘忠伟, 章毓晋. 十种基于颜色特征图像检索算法的比较和分析. 信号处理, 2000, 16(1):79-84.
LIU Z W, ZHANG Y J. A comparitive and analysis study of ten color feature-based image retrieval Algorithms. Signal Processing, 2000, 16(1): 79-84. (in Chinese)
[29] DALAL N, TRIGGS B. Histograms of oriented gradients for human detection// Proceedings of the Ieee Computer Society Conference on Computer Vision and Pattern Recognition, 2005: 886-893.
[30] 罗飞, 王国胤, 杨勇. 一种基于Gabor小波特征的人脸表情识别新方法. 计算机科学, 2009, 36(1): 181-183.
LUO F, WANG G Y, YANG Y. New approach for facial expression recognition based on Gabor features. Computer Science, 2009, 36(1): 181-183. (in Chinese)
[31] FENG X, PIETIKAINEN M, HADID A. Facial expression recognition with local binary patterns and linear programming. Pattern Recognition & Image Analysis, 2008, 15(2): 546-548.
[32] 丁世飞, 齐丙娟, 谭红艳. 支持向量机理论与算法研究综述. 电子科技大学学报, 2011, 40(1): 2-10.
DING S F, QI B J, TAN H Y. An overview on theory and algorithm of support vector machine. Journal of University of Electronic Science and Technology of China, 2011, 40(1): 2-10. (in Chinese)
[33] 李文勇, 李明, 陈梅香, 钱建平, 孙传恒. 基于机器视觉的作物多姿态害虫特征提取与分类方法. 农业工程学报, 2014, 30(14): 154-162.
LI W Y, LI M, CHEN M X, QIAN J P, SUN C H. Orchard pest automated identification method based on posture description. Transactions of the Chinese Society of Agricultural Engineering, 2014, 30(14): 154-162. (in Chinese)
[34] 李文斌. 水稻害虫图像识别技术研究. 安徽农业科学, 2014, 13(23): 8043-8045.
LI W B. Research for rice pests image recognition technology. Journal of Anhui Agricultural Sciences, 2014, 13(23): 8043-8045. (in Chinese)
[35] 路静. 基于稀疏表征的储粮害虫分类识别[D]. 郑州: 河南工业大学, 2014.
LU J. The recognition of stored grain pests based on sparse representation[D]. Zhengzhou: Henan University of Technology, 2014. (in Chinese)
[36] SINGH C B, JAYAS D S, PALIWAL J, WHITE N D G. Detection of insect-damaged wheat kernels using near-infrared hyperspectral imaging. Journal of Stored Products Research, 2009, 45(3): 151-158.
[37] 唐强. 基于图像模式识别技术的昆虫识别研究[D]. 昆明: 昆明理工大学, 2006.
TANG Q. Research on insect recognition based on image pattern recognition technology[D]. Kunming: Kunming University of Science and Technology, 2006. (in Chinese)
[38] 于合龙. 贝叶斯网在农业智能系统中的应用研究[D]. 长春: 吉林大学, 2005.
YU H L. Research on the application of bayesian network in agriculture intelligent system[D]. Changchun: Jilin University, 2005. (in Chinese)
[39] ELHAMIFAR E, VIDAL R. Robust classification using structured sparse representation//Proceedings of the Ieee Computer Society Conference on Computer Vision and Pattern Recognition, 2011: 1873-1879.
[40] ZHANG T, GHANEM B, LIU S, XU C S, AHUJA N. Low-rank sparse coding for image classification//Proceedings of the Ieee International Conference on Computer Vision, 2013: 281-288. |