Multi‐task fully convolutional networks for building segmentation on SAR image-Reference-Cited by-同舟云学术

Multi‐task fully convolutional networks for building segmentation on SAR image

Published:2019-09-18 Issue:20 Volume:2019 Page:7074-7077
ISSN:2051-3305
Container-title:The Journal of Engineering
language:en
Short-container-title:J. eng.

Author:

Zhang Zenghui¹,Guo Weiwei¹,Yu Wenhao¹,Yu Wenxian¹

Affiliation:

1. Shanghai Key Laboratory of Intelligent Sensing and RecognitionSchool of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240People's Republic of China

Publisher

Institution of Engineering and Technology (IET)

Subject

General Engineering,Energy Engineering and Power Technology,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/joe.2019.0569

Reference10 articles.

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2. YangS. ZhangQ. YuanX.et al.: ‘Superpixel‐based classification using semantic information for polarimetric SAR imagery’.2017 IEEE Int. Geoscience and Remote Sensing Symp. (IGARSS) Fort Worth TX 2017 pp.3700–3703

3. KrizhevskyA. SutskeverI. HintonG.: ‘Imagenet classification with deep convolutional neural networks’.International Conference on Neural Information Processing Systems NIPS Lake Tahoe NV USA 2012 pp.1097–1105

4. SimonyanK. ZissermanA.: ‘Very deep convolutional networks for large scale image recognition’.International Conference on Learning Representations ICLR San Diego CA USA 2015 pp.1–14

5. LinT.‐Y. MaireM. BelongieS.et al.: ‘Microsoft COCO: common objects in context’.European Conference on Computer Vision ECCV Zürich Switzerland 2014 pp.740–755

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