自动化技术、计算机技术 |
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用于图像分类的卷积神经网络中激活函数的设计 |
王红霞( ),周家奇,辜承昊,林泓*( ) |
武汉理工大学 计算机科学与技术学院,湖北 武汉 430063 |
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Design of activation function in CNN for image classification |
Hong-xia WANG( ),Jia-qi ZHOU,Cheng-hao GU,Hong LIN*( ) |
School of Computer Science and Technology, Wuhan University of Technology, Wuhan 430063, China |
引用本文:
王红霞,周家奇,辜承昊,林泓. 用于图像分类的卷积神经网络中激活函数的设计[J]. 浙江大学学报(工学版), 2019, 53(7): 1363-1373.
Hong-xia WANG,Jia-qi ZHOU,Cheng-hao GU,Hong LIN. Design of activation function in CNN for image classification. Journal of ZheJiang University (Engineering Science), 2019, 53(7): 1363-1373.
链接本文:
http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2019.07.016
或
http://www.zjujournals.com/eng/CN/Y2019/V53/I7/1363
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1 |
黄凯奇, 任伟强, 谭铁牛 图像物体分类与检测算法综述[J]. 计算机学报, 2014, 36 (6): 1225- 1240 HUANG Kai-qi, REN Wei-qiang, TAN Tie-niu A review on image object classification and detection[J]. Chinese Journal of Computers, 2014, 36 (6): 1225- 1240
|
2 |
常亮, 邓小明, 周明全, 等 图像理解中的卷积神经网络[J]. 自动化学报, 2016, 42 (9): 1300- 1312 CHANG Liang, DENG Xiao-ming, ZHOU Ming-quan, et al Convolution neural network in image understanding[J]. Acta Automatica Sinica, 2016, 42 (9): 1300- 1312
|
3 |
吴正文. 卷积神经网络在图像分类中的应用研究[D]. 成都: 电子科技大学, 2015. WU Zheng-wen. Application of convolution neural network in image classification [D]. Chengdu: University of Electronic Science and Technology of China, 2015.
|
4 |
KRIZHEVSKY A, SUTSKEVER I, HINTON G E. ImageNet classification with deep convolutional neural networks [C] // International Conference on Neural Information Processing Systems. Lake Tahoe: Springer, 2012: 1097-1105.
|
5 |
NAIR V, HINTON G E. Rectified linear units improve restricted Boltzmann machines [C] // Proceedings of the 27th International Conference on Machine Learning (ICML-10). Haifa: Omnipress, 2010: 807-814.
|
6 |
DOLEZEL P, SKRABANEK P, GAGO L Weight initialization possibilities for feedforward neural network with linear saturated activation functions[J]. IFAC-PapersOnLine, 2016, 49 (25): 49- 54
doi: 10.1016/j.ifacol.2016.12.009
|
7 |
MAAS A L, HANNUN A Y, NG A Y. Rectifier nonlinearities improve neural network acoustic models [C] // Proceedings of the 30th International Conference on Machine Learning. Atlanta: ACM, 2013: 456-462.
|
8 |
CLEVERT D A, UNTERTHINER T, HOCHREITER S Fast and accurate deep network learning by exponential linear units (ELUs)[J]. Computer Science, 2015, 5 (2): 716- 730
|
9 |
HE K, ZHANG X, REN S, et al. Delving deep into rectifiers: surpassing human-level performance on ImageNet classification [C] // Proceedings of the IEEE international conference on computer vision. Santiago: IEEE, 2015: 1026-1034.
|
10 |
石琪. 基于卷积神经网络图像分类优化算法的研究与验证[D]. 北京: 北京交通大学, 2017. SHI Qi. Research and verification of image classification optimization algorithm based on convolutional neural network [D]. Beijing: Beijing Jiaotong University, 2017.
|
11 |
LECUN Y, BOTTOU L, BENGIO Y, et al Gradient-based learning applied to document recognition[J]. Proceedings of the IEEE, 1998, 86 (11): 2278- 2324
doi: 10.1109/5.726791
|
12 |
Microsoft Research: product image categorization data set (PI 100)[DB/OL]. [2010-11-01]. http://research.microsoft.com/en-us/people/xingx/pi100.aspx.
|
13 |
FERRARI V, JURIE F, SCHMID C From images to shape models for object detection[J]. International Journal of Computer Vision, 2010, 87 (3): 284- 303
doi: 10.1007/s11263-009-0270-9
|
14 |
GRIFFIN G, HOULUB A, PERONA P. The Caltech-256. Technical report [R]. Pasadena: California Institute of Technology, 2007.
|
15 |
李明威. 图像分类中的卷积神经网络方法研究 [D]. 南京: 南京邮电大学, 2016. LI Ming-wei. Research of convolutional neural network in image classification [D]. Nanjing: Nanjing University of Posts and Telecommunications, 2016.
|
16 |
DUDA R O, HART P E, STORK D G. Pattern classification [M]. [S.l.]: Wiley, 2004.
|
17 |
贾世杰. 基于内容的商品图像分类方法研究[D]. 大连: 大连理工大学, 2013. JIA Shi-jie. Research on content based classification of commodity image [D]. Dalian: Dalian University of Technology, 2013.
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