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Widening residual skipped network for semantic segmentation
Su, Wen1,2; Wang, Zengfu1,2
2017-10-01
发表期刊IET IMAGE PROCESSING
卷号11期号:10页码:880-887
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
资助者National Natural Science Foundation of China(61472393) ; National Natural Science Foundation of China(61472393)
DOI10.1049/iet-ipr.2017.0070
收录类别SCI
语种英语
资助者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
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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
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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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