dr. Shaoguang Huang
- Work address
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Sint-Pietersnieuwstraat 41
9000 Gent - Shaoguang.Huang@UGent.be
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- Conference Paper
- open access
A deep-neural-network-based hybrid method for semi-supervised classification of polarimetric SAR data
(2019) -
Sparse coding for the analysis of high-dimensional data : applications in remote sensing and art investigation
(2019) -
Deep learning for paint loss detection with a multiscale, translation invariant network
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Landmark-based large-scale sparse subspace clustering method for hyperspectral images
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Robust dynamic classifier selection for remote sensing image classification
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Semisupervised sparse subspace clustering method with a joint sparsity constraint for hyperspectral remote sensing images
(2019) IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING. 12(3). p.989-999 -
- Conference Paper
- C3
- open access
Deep Learning for Paint Loss Detection: A Case Study on the Ghent Altarpiece
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Joint sparsity based sparse subspace clustering for hyperspectral images
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- Conference Paper
- C1
- open access
Paint loss detection via kernel sparse representation
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- Journal Article
- A1
- open access
A robust sparse representation model for hyperspectral image classification