50 search results - page 1 / 10 » Information Theoretical Kernels for Generative Embeddings Ba... |
SSPR
2010
Springer
13 years 2 months ago
2010
Springer
Many approaches to learning classifiers for structured objects (e.g., shapes) use generative models in a Bayesian framework. However, state-of-the-art classifiers for vectorial d...
EMMCVPR
2009
Springer
13 years 11 months ago
2009
Springer
Generative kernels represent theoretically grounded tools able to increase the capabilities of generative classification through a discriminative setting. Fisher Kernel is the fi...
ICIP
2010
IEEE
13 years 2 months ago
2010
IEEE
Most approaches to learn classifiers for structured objects (e.g., images) use generative models in a classical Bayesian framework. However, state-of-the-art classifiers for vecto...
CVPR
2010
IEEE
13 years 10 months ago
2010
IEEE
Visual vocabulary serves as a fundamental component in many computer vision tasks, such as object recognition, visual search, and scene modeling. While state-of-the-art approaches...
ECML
2004
Springer
13 years 10 months ago
2004
Springer
One approach to improve the accuracy of classifications based on generative models is to combine them with successful discriminative algorithms. Fisher kernels were developed to c...