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» More generality in efficient multiple kernel learning
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199
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ICRA
2009
IEEE
175views Robotics» more  ICRA 2009»
15 years 3 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...
ILP
2007
Springer
15 years 12 months ago
A Phase Transition-Based Perspective on Multiple Instance Kernels
: This paper is concerned with relational Support Vector Machines, at the intersection of Support Vector Machines (SVM) and relational learning or Inductive Logic Programming (ILP)...
Romaric Gaudel, Michèle Sebag, Antoine Corn...
175
Voted
FLAIRS
2004
15 years 7 months ago
A Faster Algorithm for Generalized Multiple-Instance Learning
In our prior work, we introduced a generalization of the multiple-instance learning (MIL) model in which a bag's label is not based on a single instance's proximity to a...
Qingping Tao, Stephen D. Scott
178
Voted
ECCV
2010
Springer
15 years 10 months ago
Kernel Sparse Representation for Image Classification and Face Recognition
Recent research has shown the effectiveness of using sparse coding(Sc) to solve many computer vision problems. Motivated by the fact that kernel trick can capture the nonlinear sim...
142
Voted
ICCV
2009
IEEE
16 years 10 months ago
Multiple Kernels for Object Detection
Our objective is to obtain a state-of-the art object category detector by employing a state-of-the-art image classifier to search for the object in all possible image subwindows....
Andrea Vedaldi, Varun Gulshan, Manik Varma, Andrew...