Spatial contextual superpixel model for natural roadside vegetation classification
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- 作者：Ligang Zhanga ; l.zhang@cqu.edu.au" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Brijesh Vermaa ; b.verma@cqu.edu.au" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; David Stockwellb ; david.r.stockwell@tmr.qld.gov.au" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae
- 关键词：Feature extraction ; Image segmentation ; Classification algorithms ; Object recognition ; Artificial neural networks
- 刊名：Pattern Recognition
- 出版年：2016
- 出版时间：December 2016
- 年：2016
- 卷：60
- 期：Complete
- 页码：444-457
- 全文大小：4141 K
文摘
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A novel Spatial Contextual Superpixel Model (SCSM) for natural vegetation classification.
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A new reverse superpixel merging strategy to progressively merge superpixels.
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High performance on challenging natural datasets and Stanford background data.