[1]谢维荪.多肉植物的新范围与新分类[J].中国花卉盆景,2012(6):14⁃15.
XIE W S.New range and classification of succulents[J].Chinese Flowers Bonsai,2012(6):14⁃15.
[2]刘俨娇.基于深度卷积网的多肉植物图像分类技术研究[D].大连:大连交通大学,2018.
LIU Y J.Image classification of succulents based on deep convolutional network [D].Dalian: Dalian Jiaotong University,2018.
[3]黄嘉宝,朱永华,周霁婷,等.基于卷积神经网络的多肉植物细粒度图像分类[J].上海大学学报(自然科学版),2020,26(2):283⁃291.
HUANG J B,ZHU Y H,ZHOU J T,et al.Fine⁃grained image classification of succulents based on convolutional neural networks[J].Journal of Shanghai University(Natural Science),2020,26(2):283⁃291.
[4]DYRMANN M,KARSTOFT H,MIDTIBY H S.Plant species classification using deep convolutional neural network[J].Biosystems Engineering,2016,151:72⁃80.
[5]HU J,CHEN Z,YANG M,et al.A multi⁃scale fusion convolutional neural network for plant leaf recognition [J].IEEE Signal Processing Letters,2018,25(6):853⁃857.
[6]LEE S H,CHAN C S,WILKIN P,et al.Deep⁃plant:Plant identification with convolutional neural networks [C]//IEEE International Conference on Image Processing.Quebec City,QC,Canada:IEEE,2015:452⁃456.
[7]KUMAR N,BELHUMEUR P N,BISWAS A,et al.Leafsnap:A computer vision system for automatic plant species identification[C]//Proceedings of the 12th European Conference on Computer Vision.Berlin Heidelberg:Springer,2012:502⁃516.
[8]李立鹏,师菲蓬,田文博,等.基于残差网络和迁移学习的野生植物图像识别方法[J].无线电工程,2021,51 (9):857⁃863.
LI L P,SHI F P,TIAN W B,et al.Wild plant image recognition method based on residual network and transfer learning[J].Radio Engineering,2021,51(9):857⁃863.
[9]HE K,FAN H,WU Y,et al.Momentum contrast for unsupervised visual representation learning[C]//IEEE Conference on Computer Vision and Pattern Recog⁃nition. Seattle,WA,USA:IEEE,2020:9726⁃9735.
[10]CHEN T,KORNBLITH S,NOROUZI M,et al.A simple framework for contrastive learning of visual representations[EB/OL].(2020⁃02⁃13)[2020⁃03⁃30].https://doi.org/10.48550/arXiv.2002.05709.
[11]SHORTEN C,KHOSHGOFTAAR T M.A survey on image data augmentation for deep learning[J].Big Data,2019,6(1):60⁃108.
[12]DEVRIES T,TAYLOR W.Improved regularization of convolutional neural networks with cutout[EB/OL].(2017⁃08⁃15)[2017⁃11⁃29].https://doi. org/10. 48550/arXiv. 1708. 04552.
[13]ZHANG H Y,CISSE M,DAUPHIN Y N,et al.Mixup:Beyond empirical risk minimization [EB/OL].(2017⁃10⁃25)[2018⁃04⁃27].https://doi.org/10.48550/arXiv.1710. 09412.
[14]ZHUANG L,MAO H,WU C,et al.A ConvNet for the 2020s[EB/OL].(2022⁃01⁃10)[2022⁃03⁃02].https://doi.org/10.48550/arXiv.2201.03545.
[15]XIE S,GIRSHICK R,DOLLAR P,et al.Aggregated residual transformations for deep neural networks[C]//IEEE Conference on Computer Vision and Pattern Recognition.Honolulu, HI,USA: IEEE,2017:5987⁃5995.
[16]LIU Z,LIN Y,CAO Y,et al.Swin transformer:Hierarchical vision transformer using shifted windows[C]//IEEE Conference on Computer Vision and Pattern Recognition.Montreal,QC,Canada:IEEE,2021:9992⁃10002.
[17]LE⁃KHAC P H,HEALY G,SMEATON A F.Contrastive representation learning:A framework and review[J].IEEE Access,2020,8:193907⁃193934.
[18]魏花.基于卷积神经网络的细粒度图像识别关键技术分析与研究[D].长春:中国科学院大学,2021.
WEI H.Analysis and research on key technologies of fine⁃grained image recognition based on convolutional neural network[D].Changchun:University of Chinese Academy of Sciences,2021.
[19]RUBINSTEIN R Y.Optimization of computer simulation models with rare events[J].European Journal of Operational Research,1997,99(1):89⁃112.
[20]LOSHCHILOV I,HUTTER F.Decoupled weight decay regularization[EB/OL].(2017⁃11⁃14)[2019⁃01⁃04].https://doi.org/10.48550/arXiv.1711.05101v3.
[21]KINGMA D,BA J.Adam:A method for stochastic optimization[EB/OL].(2014⁃12⁃22)[2015⁃06⁃23].https://doi.org/10.48550/arXiv.1412.6980v6.
[22]HE K,ZHANG X Y,REN S Q,et al.Deep residual learning for image recognition[C]//IEEE Conference on Computer Vision and Pattern Recognition.Las Vegas,NV,USA:IEEE,2016:770⁃778.
[23]LOSHCHILOV I,HUTTER F.SGDR:Stochastic gradient descent with warm restarts[EB/OL].(2016⁃08⁃13)
[2017⁃02⁃23].https://doi.org/10.48550/arXiv.1608.03983v3.
[24]DOSOVITSKIY A,BEYER L,KOLESNIKOV A,et al.An image is worth 16x16 words:Transformers for image recognition at scale[EB/OL].(2020⁃10⁃22)[2021⁃06⁃03].https://doi.org/10.48550/arXiv.2010.11929.
[25]HE T,ZHANG Z,ZHANG H,et al.Bag of Tricks for image classification with convolutional neural networks[C]//IEEE Conference on Computer Vision and Pattern Recognition(CVPR).Long Beach,CA,USA:IEEE,2019:558⁃567.
[26]HUANG G,SUN Y.Deep networks with stochastic depth [C]//Computer Vision⁃ECCV 2016. Cham:Springer International Publishing,2016:646⁃661.
[27]NILSBACK M E,ZISSERMAN A.Automated flower classification over a large number of classes[C]//Sixth Indian Conference on Computer Vision,Graphics&Image Processing. Bhubaneswar,India:IEEE,2008:16⁃19.
[28]WELINDER P,BRANSON S,MITA T,et al.Caltech⁃UCSD birds 200[J/OL].California Institute of Technology,2010 [2023⁃02⁃10].https://authors.library.caltech. edu/27452/.
[29]ADITYA K,NITYANANDA J,YAO B P,et al.Novel dataset for fine⁃grained image categorization:stanford dogs[C]//IEEE Conference on Computer Vision and Pattern Recognition(CVPR).Colorado Springs,CO,USA:IEEE,2011.
|