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» The Necessity of Combining Adaptation Methods
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ECCV
2008
Springer
14 years 12 months ago
Semi-supervised On-Line Boosting for Robust Tracking
Abstract. Recently, on-line adaptation of binary classifiers for tracking have been investigated. On-line learning allows for simple classifiers since only the current view of the ...
Helmut Grabner, Christian Leistner, Horst Bischof
CVPR
2004
IEEE
14 years 12 months ago
Bayesian Face Recognition Using Support Vector Machine and Face Clustering
In this paper, we first develop a direct Bayesian based Support Vector Machine by combining the Bayesian analysis with the SVM. Unlike traditional SVM-based face recognition metho...
Zhifeng Li, Xiaoou Tang
ICBA
2004
Springer
207views Biometrics» more  ICBA 2004»
14 years 3 months ago
Dynamic Local Feature Analysis for Face Recognition
This paper introduces an innovative method, Dynamic Local Feature Analysis (DLFA), for human face recognition. In our proposed method, the face shape and the facial texture informa...
Johnny Ng, Humphrey Cheung
PKDD
2009
Springer
138views Data Mining» more  PKDD 2009»
14 years 4 months ago
Margin and Radius Based Multiple Kernel Learning
A serious drawback of kernel methods, and Support Vector Machines (SVM) in particular, is the difficulty in choosing a suitable kernel function for a given dataset. One of the appr...
Huyen Do, Alexandros Kalousis, Adam Woznica, Melan...
ICES
2010
Springer
277views Hardware» more  ICES 2010»
13 years 8 months ago
An Efficient, High-Throughput Adaptive NoC Router for Large Scale Spiking Neural Network Hardware Implementations
Recently, a reconfigurable and biologically inspired paradigm based on network-on-chip (NoC) and spiking neural networks (SNNs) has been proposed as a new method of realising an ef...
Snaider Carrillo, Jim Harkin, Liam McDaid, Sandeep...