A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation

doi:10.1007/s11633-017-1053-3

CASIA OpenIR > 学术期刊 > Machine Intelligence Research

	A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation
	Bo Zhao1,2 ; Jiashi Feng 2; Xiao Wu 1; Shuicheng Yan 2
发表期刊	International Journal of Automation and Computing
ISSN	1476-8186
	2017
卷号	14 期号:2 页码:119-135
文章类型	IJAC-2016-07-171.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 fine-grained image classification 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 fine-grained image classification 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 classi¯cation semantic segmentation convolutional neural network (CNN) recurrent neural network (RNN).
DOI	10.1007/s11633-017-1053-3
引用统计	被引频次：180[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/173211/42470
专题	学术期刊_Machine Intelligence Research
作者单位	1.School of Information Science and Technology, Southwest Jiaotong University, Chengdu 613000, China 2.Department of Electrical and Computer Engineering, National University of Singapore, 117583, Singapore
推荐引用方式 GB/T 7714	Bo Zhao,Jiashi Feng,Xiao Wu,et al. A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation[J]. International Journal of Automation and Computing,2017,14(2):119-135.
APA	Bo Zhao,Jiashi Feng,Xiao Wu,&Shuicheng Yan.(2017).A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation.International Journal of Automation and Computing,14(2),119-135.
MLA	Bo Zhao,et al."A Survey on Deep Learning-based Fine-grained Object Classification and Semantic Segmentation".International Journal of Automation and Computing 14.2(2017):119-135.

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