Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 226-229.
• Pattem Recognition & Image Processing • Previous Articles Next Articles
WEI Yang, BI Xiu-li, XIAO Bin
CLC Number:
[1]ESTRUCH J J,CAROZZI N B,DESAI N,et al.Transgenic plants:an emerging approach to pest control [J].Nature Biotechnology,1997,15(2):137-141. [2]LI Y,XIA C,LEE J.Detection of small-sized insect pest in greenhouses based on multifractal analysis [J].Optik-International Journal for Light and Electron Optics,2015,126(19):2138-2143. [3]PARSA S,MORSE S,BONIFACIO A,et al.Obstacles to integrated pest management adoption in developing countries [J].Proceedings of the National Academy of Sciences,2014,111(10):3889-3894. [4]MUNDADA R G,GOHOKAR V.Detection and classification of pests in greenhouse using image processing [J].IOSR Journal of Electronics and Communication Engineering,2013,5(6):57-63. [5]CORTES C,VAPNIK V.Support-vector networks [J].Machine Learning,1995,20(3):273-297. [6]KRIZHEVSKY A,SUTSKEVER I,HINTON G E.Imagenet classification with deep convolutional neural networks[C]∥Proceedings of the Advances in Neural Information Processing Systems.2012. [7]OORD A V D,KALCHBRENNER N,KAVUKCUOGLU K.Pixel recurrent neural networks [J/OL].https://cn.arXiv.org/abs/1601.06759. [8]RADFORD A,METZ L,CHINTALA S.Unsupervised representation learning with deep convolutional generative adversarial networks [J/OL].https://arxiv.org/abs/1511.06434. [9]REN S,HE K,GIRSHICK R,et al.Faster R-CNN:Towards real-time object detection with region proposal networks[C]∥Proceedings of the Advances in Neural Information Processing Systems.2015. [10]LIU Z,GAO J,YANG G,et al.Localization and Classification of Paddy Field Pests using a Saliency Map and Deep Convolutional Neural Network [J].Scientific reports,2016,6:20410. [11]METZ A R L,RESEARCH I,BOSTON M,et al.Very deep convolutional networks for large-scale image recognition[J/OL].https://www.researchgate.net/publication/294284631_Localization_and_Classification_of_Paddy_Field_Pests_using_a_Saliency_Map_and_Deep_Convolutional_Neural_Network. [12]GIRSHICK R.Fast r-cnn[C]∥Proceedings of the IEEE International Conference on Computer Vision.2015. [13]RUMELHART D E,HINTON G E,WILLIAMS R J.Learning representations by back-propagating errors [J].Cognitive mo-deling,1988,5(3):1. [14]CARPENTER B.Lazy sparse stochastic gradient descent for regularized multinomial logistic regression[J/OL].https://www.mendeley.com/research-papers/lazy-sparse-stochastic-gradient-descent-regularized-multinomial-logistic-regression. [15]HE K,GKIOXARI G,DOLLAR P,et al.Mask R-CNN[J]. IEEE Transactions on Pattern Analysis & Machine Intelligence,2017,PP(99):1. [16]KOHAVI R.A study of cross-validation and bootstrap for accuracy estimation and model selection[C]∥Proceedings of the Ljcai.Stanford,CA,1995. |
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