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Why and When Can Deep-but Not Shallow-networks Avoid the Curse of Dimensionality: A Review
Tomaso Poggio1; Hrushikesh Mhaskar2,3; Lorenzo Rosasco1; Brando Miranda1; Qianli Liao1
发表期刊International Journal of Automation and Computing
ISSN1476-8186
2017
卷号14期号:5页码:503-519
文章类型IJAC-HIC-2016-11-271.pdf
摘要The deep learning technology has shown impressive performance in various vision tasks such as image classification, object detection and semantic segmentation. In particular, recent advances of deep learning techniques bring encouraging performance to ¯ne-grained image classi¯cation which aims to distinguish subordinate-level categories, such as bird species or dog breeds. This task is extremely challenging due to high intra-class and low inter-class variance. In this paper, we review four types of deep learning based fine-grained image classification approaches, including the general convolutional neural networks (CNNs), part detection based, ensemble of networks based and visual attention based ¯ne-grained image classi¯cation approaches. Besides, the deep learning based semantic segmentation approaches are also covered in this paper. The region proposal based and fully convolutional networks based approaches for semantic segmentation are introduced respectively.
关键词Deep learning fine-grained image classification semantic segmentation convolutional neural network (CNN) recurrent neural network (RNN).
DOI10.1007/s11633-017-1054-2
引用统计
被引频次:178[WOS]   [WOS记录]     [WOS相关记录]
文献类型期刊论文
条目标识符http://ir.ia.ac.cn/handle/173211/42475
专题学术期刊_Machine Intelligence Research
作者单位1.Center for Brains, Minds, and Machines, McGovern Institute for Brain Research, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
2.Department of Mathematics, California Institute of Technology, Pasadena, CA 91125, USA
3.Institute of Mathematical Sciences, Claremont Graduate University, Claremont, CA 91711, USA
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Tomaso Poggio,Hrushikesh Mhaskar,Lorenzo Rosasco,et al. Why and When Can Deep-but Not Shallow-networks Avoid the Curse of Dimensionality: A Review[J]. International Journal of Automation and Computing,2017,14(5):503-519.
APA Tomaso Poggio,Hrushikesh Mhaskar,Lorenzo Rosasco,Brando Miranda,&Qianli Liao.(2017).Why and When Can Deep-but Not Shallow-networks Avoid the Curse of Dimensionality: A Review.International Journal of Automation and Computing,14(5),503-519.
MLA Tomaso Poggio,et al."Why and When Can Deep-but Not Shallow-networks Avoid the Curse of Dimensionality: A Review".International Journal of Automation and Computing 14.5(2017):503-519.
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