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ICPR
2008
IEEE
15 years 10 months ago
Human tracking based on Soft Decision Feature and online real boosting
Online Boosting is an effective incremental learning method which can update weak classifiers efficiently according to the object being trackedt. It is a promising technique for o...
Hironobu Fujiyoshi, Masato Kawade, Shihong Lao, Ta...
ALT
2010
Springer
14 years 11 months ago
Online Multiple Kernel Learning: Algorithms and Mistake Bounds
Online learning and kernel learning are two active research topics in machine learning. Although each of them has been studied extensively, there is a limited effort in addressing ...
Rong Jin, Steven C. H. Hoi, Tianbao Yang
ICASSP
2011
IEEE
14 years 1 months ago
Online feature selection and classification
This paper presents an online feature selection and classification algorithm. The algorithm is implemented for impact acoustics signals to sort hazelnut kernels. The classifier, w...
Habil Kalkan, Bayram Cetisli
CVPR
2005
IEEE
15 years 11 months ago
Online Detection and Classification of Moving Objects Using Progressively Improving Detectors
Boosting based detection methods have successfully been used for robust detection of faces and pedestrians. However, a very large amount of labeled examples are required for train...
Omar Javed, Saad Ali, Mubarak Shah
CVPR
2010
IEEE
15 years 5 months ago
On-line Semi-supervised Multiple-Instance Boosting
A recent dominating trend in tracking called tracking-by-detection uses on-line classifiers in order to redetect objects over succeeding frames. Although these methods usually deli...
Bernhard Zeisl, Christian Leistner, Amir Saffari, ...