Widening residual skipped network for semantic segmentation

doi:10.1049/iet-ipr.2017.0070

	Widening residual skipped network for semantic segmentation
	Su, Wen 1,2; Wang, Zengfu1,2
	2017-10-01
发表期刊	IET IMAGE PROCESSING
摘要	Over the past two years deep convolutional neural networks have pushed the performance of computer vision systems to soaring heights on semantic segmentation. In this study, the authors present a novel semantic segmentation method of using a deep fully convolutional neural network to achieve image segmentation results with more precise boundary localisation. The above segmentation engine is trainable, and consists of an encoder network with widening residual skipped connections and a decoder network with a pixel-wise classification layer. Here the encoder network with widening residual skipped connections allows the combination of shallow layer features and deep layer semantic features, and the decoder network with classification layer maps the low-resolution encoder features to full resolution image with pixel-wise classification. The experimental results on PASCAL VOC 2012 semantic segmentation dataset and Cityscapes dataset show that the proposed method is effective and competitive.
文章类型	Article
WOS标题词	Science & Technology ; Technology
DOI	10.1049/iet-ipr.2017.0070
收录类别	SCI
语种	英语
项目资助者	National Natural Science Foundation of China(61472393) ; National Natural Science Foundation of China(61472393) ; National Natural Science Foundation of China(61472393) ; National Natural Science Foundation of China(61472393)
WOS研究方向	Computer Science ; Engineering ; Imaging Science & Photographic Technology
WOS类目	Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic ; Imaging Science & Photographic Technology
WOS记录号	WOS:000413198200010
引用统计	被引频次：8[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.hfcas.ac.cn:8080/handle/334002/33828
专题	中科院合肥智能机械研究所
作者单位	1.Chinese Acad Sci, Inst Intelligent Machines, Hefei, Anhui, Peoples R China 2.Univ Sci & Technol China, Dept Automat, Hefei, Anhui, Peoples R China
推荐引用方式 GB/T 7714	Su, Wen,Wang, Zengfu. Widening residual skipped network for semantic segmentation[J]. IET IMAGE PROCESSING,2017,11(10):880-887.
APA	Su, Wen,&Wang, Zengfu.(2017).Widening residual skipped network for semantic segmentation.IET IMAGE PROCESSING,11(10),880-887.
MLA	Su, Wen,et al."Widening residual skipped network for semantic segmentation".IET IMAGE PROCESSING 11.10(2017):880-887.

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Widening residual sk（4950KB）	期刊论文	作者接受稿	开放获取	CC BY-NC-SA	浏览下载