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» Multiple Kernels for Object Detection
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ICRA
2009
IEEE
175views Robotics» more  ICRA 2009»
13 years 6 months ago
A combination of particle filtering and deterministic approaches for multiple kernel tracking
Color-based tracking methods have proved to be efficient for their robustness qualities. The drawback of such global representation of an object is the lack of information on its s...
Céline Teuliere, Éric Marchand, Laur...
ICDM
2009
IEEE
174views Data Mining» more  ICDM 2009»
14 years 3 months ago
Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis
—We consider the problem of learning a linear combination of pre-specified kernel matrices in the Fisher discriminant analysis setting. Existing methods for such a task impose a...
Fei Yan, Josef Kittler, Krystian Mikolajczyk, Muha...
SP
2007
IEEE
107views Security Privacy» more  SP 2007»
14 years 3 months ago
Lurking in the Shadows: Identifying Systemic Threats to Kernel Data
The integrity of kernel code and data is fundamental to the integrity of the computer system. Tampering with the kernel data is an attractive venue for rootkit writers since malic...
Arati Baliga, Pandurang Kamat, Liviu Iftode
ICPR
2008
IEEE
14 years 10 months ago
Multiple kernel learning from sets of partially matching image features
Abstract: Kernel classifiers based on Support Vector Machines (SVM) have achieved state-ofthe-art results in several visual classification tasks, however, recent publications and d...
Guo ShengYang, Min Tan, Si-Yao Fu, Zeng-Guang Hou,...
ICPR
2010
IEEE
14 years 3 months ago
Object Recognition and Localization Via Spatial Instance Embedding
—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...
Nazli Ikizler Cinbis, Stan Sclaroff