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PreviewIssue DateTitleAuthor(s)
2012Positive semidefinite metric learning using boosting-like algorithmsShen, C.; Kim, J.; Wang, L.; Van Den Hengel, A.
2014Fast supervised hashing with decision trees for high-dimensional dataLin, G.; Shen, C.; Shi, Q.; Van Den Hengel, A.; Suter, D.; IEEE Conference on Computer Vision and Pattern Recognition (2014 : Columbus, Ohio)
2013Training effective node classifiers for cascade classificationShen, C.; Wang, P.; Paisitkriangkrai, S.; Van Den Hengel, A.
2013Approximate least trimmed sum of squares fitting and applications in image analysisShen, F.; Shen, C.; Van Den Hengel, A.; Tang, Z.
2013Incremental learning of 3D-DCT compact representations for robust visual trackingLi, X.; Dick, A.; Shen, C.; Van Den Hengel, A.; Wang, H.
2013Learning compact binary codes for visual trackingLi, X.; Shen, C.; Dick, A.; Van Den Hengel, A.; IEEE Conference on Computer Vision and Pattern Recognition (26th : 2013 : Portland, Oregon)
2012Non-sparse linear representations for visual tracking with online reservoir metric learningLi, X.; Shen, C.; Shi, Q.; Dick, A.; Van Den Hengel, A.; IEEE Conference on Computer Vision and Pattern Recognition (25th : 2012 : Providence, Rhode Island)
2013Context-aware hypergraph construction for robust spectral clusteringLi, X.; Hu, W.; Shen, C.; Dick, A.; Zhang, Z.
2014Large-margin learning of compact binary image encodingsPaisitkriangkrai, S.; Shen, C.; Van Den Hengel, A.
2012Sharing features in multi-class boosting via group sparsityPaisitkriangkrai, S.; Shen, C.; Van Den Hengel, A.; IEEE Conference on Computer Vision and Pattern Recognition (25th : 2012 : Providence, Rhode Island)

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