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Results 1-10 of 16 (Search time: 0.002 seconds).
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PreviewIssue DateTitleAuthor(s)
2013Approximate least trimmed sum of squares fitting and applications in image analysisShen, F.; Shen, C.; Van Den Hengel, A.; Tang, Z.
2012Positive semidefinite metric learning using boosting-like algorithmsShen, C.; Kim, J.; Wang, L.; Van Den Hengel, A.
2013Shape similarity analysis by self-tuning locally constrained mixed-diffusionLuo, L.; Shen, C.; Zhang, C.; Van Den Hengel, A.
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)
2011Is face recognition really a compressive sensing problem?Shi, Q.; Eriksson, A.; Van Den Hengel, A.; Shen, C.; Conference on Computer Vision and Pattern Recognition (2011 : Rhode Island, USA)
2014Large-margin learning of compact binary image encodingsPaisitkriangkrai, S.; Shen, C.; Van Den Hengel, A.
2012Is margin preserved after random projection?Shi, Q.; Shen, C.; Hill, R.; Van Den Hengel, A.; International Conference on Machine Learning (29th : 2012 : Edinburgh, Scotland)
2013Incremental learning of 3D-DCT compact representations for robust visual trackingLi, X.; Dick, A.; Shen, C.; Van Den Hengel, A.; Wang, H.
2013Fully corrective boosting with arbitrary loss and regularizationShen, C.; Li, H.; Van Den Hengel, A.
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)