Computer Science ›› 2022, Vol. 49 ›› Issue (11A): 211200009-6.doi: 10.11896/jsjkx.211200009
• Image Processing & Multimedia Technology • Previous Articles Next Articles
DENG Peng-fei, GUAN Zheng, WANG Yu-yang, WANG Xue
CLC Number:
[1]MENG Y,CHEN G F,LU J,et el.Simulink platform real-time diagnosis in the video image of corn diseases[J].Journal of Jilin Agricultural University,2017,39(4):483-487. [2]LV G Z,CHEN J,BAI J K,at el.Present situation and control measures of corn diseases in China[J].Plant Protection,1997,23(4):20-21. [3]MILLER S A,BEED F D,HARMON C L.Plant disease diagnostic capabilities and networks[J].Annual Review of Phytopathology,2009,47(1):15-38. [4]LI Q Q,GUO M K,GUO C,et al.Occurrence dynamics of maize diseases in Gansu Province[J].Plant Protection,2014,40(3):161-164. [5]KUSSUL N,LAVRENIUK M,SKAKUN S,et al.Deep learning classification of land cover and crop typs using remote sensing data[J/OL].IEEE Geoscience and Remote Sensing Letters,2017,PP(99):1-5.https://xueshu.baidu.com/usercenter/paper/show?paperid=b525470daa7f9623c2f138d8cca55d17&site=xueshu_se. [6]KRIZHEVSKY A,SUTSKEVER I,HINTON G.ImageNetclassifica-tion with deep convolutional neural networks[J].Advances in Neural Information Processing Systems,2012,25(2):1097-1105. [7]SIMONYAN K,ZISSERMAN A.Very deep convolutional networks for large-scale image recognition[J].arXiv:1409.1556,2014. [8]SZEGEDY C,LIU W,JIA Y,et al.Going deeper with convolutions[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2015:1-9. [9]HE K,ZHANG S R,SUN J.Deep residual learning forimage recognition[C]//Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition.2015:770-778. [10]YANG Y,ZHANG Y L,MIAO W,et al.Accurate identification and location of corn rhizome based on Faster R-CNN[J].Transactions of the Chinese Society for Agricultural Machinery,2018,49(10):46-53. [11]GAO Y,GUO J L,LI X,et al.Instance-level segmentationmethod for group pig images based on deep learning[J].Transactions of the Chinese Society for Agricultural Machinery,2019,50(4):179-187. [12]BI S,GAO F,CHEN J W,et al.Detection method of citrus based on deep convolution neural network[J].Transacions of the Chinese Society for Agricultural Machinery,2019,50(5):181-186. [13]LIU Y B,LEI B,CAO Y,et al.Recognition of maize disease based on deep convolutional Neural network[J].Chinese Agricultural Science Bulletin,2018,34(36):15-9-164. [14]YANG M Y,ZHANG Y G,LIU T.Small sample recognition of maize disease based on convolutional neural network[J].Chinese Journal of Eco-Agriculture(Chinese and English),2020,28(12):1924-1931. [15]XU Y,ZHAO B,ZHAI Y,et al.Maize Diseases Identification Method Based on Multi-Scale Convolutional Global Pooling Neural Network[J].IEEE Access,2021,9:27959-27970. [16]HAN S,MAO H Z,DALLY W J.Deep compression:com-pressing deep neural networks with pruning,trained quantization and huffman coding[J].Fiber,2015,56(4):3-7. [17]HINTON G,VINYALS O,DEAN J.Distilling the knowledge in a neural network[J].arXiv:1503.02531,2014. |
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