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111
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ICASSP
2008
IEEE
15 years 7 months ago
Hybrid feature selection for gesture recognition using support vector machines
This paper presents an approach for a multi-cue based two-dimensional gesture recognition that combines two different forms of cues, namely shape cues and motion cues, in a suppor...
Yu Yuan, Kenneth Barner
94
Voted
DASFAA
2007
IEEE
143views Database» more  DASFAA 2007»
15 years 7 months ago
Using Redundant Bit Vectors for Near-Duplicate Image Detection
Images are amongst the most widely proliferated form of digital information due to affordable imaging technologies and the Web. In such an environment, the use of digital watermar...
Jun Jie Foo, Ranjan Sinha
108
Voted
ISSRE
2005
IEEE
15 years 6 months ago
A Novel Method for Early Software Quality Prediction Based on Support Vector Machine
The software development process imposes major impacts on the quality of software at every development stage; therefore, a common goal of each software development phase concerns ...
Fei Xing, Ping Guo, Michael R. Lyu
83
Voted
FCCM
1999
IEEE
111views VLSI» more  FCCM 1999»
15 years 5 months ago
Optimizing FPGA-Based Vector Product Designs
This paper presents a method, called multiple constant multiplier trees MCMTs, for producing optimized recon gurable hardware implementations of vector products. An algorithm for ...
Dan Benyamin, John D. Villasenor, Wayne Luk
COLT
1999
Springer
15 years 5 months ago
Covering Numbers for Support Vector Machines
—Support vector (SV) machines are linear classifiers that use the maximum margin hyperplane in a feature space defined by a kernel function. Until recently, the only bounds on th...
Ying Guo, Peter L. Bartlett, John Shawe-Taylor, Ro...