Adelaide Research & Scholarship: Search

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Preview	Issue Date	Title	Author(s)
	2011	A direct formulation for totally-corrective multi-class boosting	Shen, C.; Hao, Z.; IEEE Conference on Computer Vision and Pattern Recognition (24th : 2011 : Colorado Springs, CO, U.S.A.)
	2013	Learning compact binary codes for visual tracking	Li, X.; Shen, C.; Dick, A.; Van Den Hengel, A.; IEEE Conference on Computer Vision and Pattern Recognition (26th : 2013 : Portland, Oregon)
	2013	Context-aware hypergraph construction for robust spectral clustering	Li, X.; Hu, W.; Shen, C.; Dick, A.; Zhang, Z.
	2012	Non-sparse linear representations for visual tracking with online reservoir metric learning	Li, X.; Shen, C.; Shi, Q.; Dick, A.; Van Den Hengel, A.; IEEE Conference on Computer Vision and Pattern Recognition (25th : 2012 : Providence, Rhode Island)
	2012	Sharing features in multi-class boosting via group sparsity	Paisitkriangkrai, S.; Shen, C.; Van Den Hengel, A.; IEEE Conference on Computer Vision and Pattern Recognition (25th : 2012 : Providence, Rhode Island)
	2012	Positive semidefinite metric learning using boosting-like algorithms	Shen, C.; Kim, J.; Wang, L.; Van Den Hengel, A.
	2014	Large-margin learning of compact binary image encodings	Paisitkriangkrai, S.; Shen, C.; Van Den Hengel, A.
	2013	Incremental learning of 3D-DCT compact representations for robust visual tracking	Li, X.; Dick, A.; Shen, C.; Van Den Hengel, A.; Wang, H.
	2013	Training effective node classifiers for cascade classification	Shen, C.; Wang, P.; Paisitkriangkrai, S.; Van Den Hengel, A.
	2014	Fast supervised hashing with decision trees for high-dimensional data	Lin, G.; Shen, C.; Shi, Q.; Van Den Hengel, A.; Suter, D.; IEEE Conference on Computer Vision and Pattern Recognition (2014 : Columbus, Ohio)