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» Image Classification Using Marginalized Kernels for Graphs
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IJCV
2007
208views more  IJCV 2007»
13 years 7 months ago
Binet-Cauchy Kernels on Dynamical Systems and its Application to the Analysis of Dynamic Scenes
We derive a family of kernels on dynamical systems by applying the Binet-Cauchy theorem to trajectories of states. Our derivation provides a unifying framework for all kernels on d...
S. V. N. Vishwanathan, Alexander J. Smola, Ren&eac...
ICCV
2003
IEEE
14 years 9 months ago
On the Use of Marginal Statistics of Subband Images
A commonly used representation of a visual pattern is the set of marginal probability distributions of the output of a bank of filters (Gaussian, Laplacian, Gabor etc...). This re...
Joshua Gluckman
WEBI
2010
Springer
13 years 5 months ago
Image Set Classification Using Multi-layer Multiple Instance Learning with Application to Cannabis Website Classification
We propose using multi-layer multiple instance learning (MMIL) for image set classification and applying it to the task of cannabis website classification. We treat each image as a...
Nianhua Xie, Haibin Ling, Weiming Hu
ICPR
2006
IEEE
14 years 8 months ago
A maximum margin discriminative learning algorithm for temporal signals
We propose a new maximum margin discriminative learning algorithm here for classification of temporal signals. It is superior to conventional HMM in the sense that it does not nee...
Wenjie Xu, Jiankang Wu, Zhiyong Huang
ICMLA
2009
13 years 5 months ago
Transformation Learning Via Kernel Alignment
This article proposes an algorithm to automatically learn useful transformations of data to improve accuracy in supervised classification tasks. These transformations take the for...
Andrew Howard, Tony Jebara