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ICPR
2006
IEEE
14 years 5 months ago
Combining Generative and Discriminative Methods for Pixel Classification with Multi-Conditional Learning
It is possible to broadly characterize two approaches to probabilistic modeling in terms of generative and discriminative methods. Provided with sufficient training data the discr...
B. Michael Kelm, Chris Pal, Andrew McCallum
IDEAL
2005
Springer
13 years 10 months ago
Evolving Neural Networks for the Classification of Malignancy Associated Changes
Malignancy Associated Changes are subtle changes to the nuclear texture of visually normal cells in the vicinity of a cancerous or precancerous lesion. We describe a classifier for...
Jennifer Hallinan
CVPR
2005
IEEE
14 years 6 months ago
Generative versus Discriminative Methods for Object Recognition
Many approaches to object recognition are founded on probability theory, and can be broadly characterized as either generative or discriminative according to whether or not the di...
Ilkay Ulusoy, Christopher M. Bishop
PR
2010
147views more  PR 2010»
13 years 3 months ago
Minimum classification error learning for sequential data in the wavelet domain
Wavelet analysis has found widespread use in signal processing and many classification tasks. Nevertheless, its use in dynamic pattern recognition have been much more restricted ...
D. Tomassi, Diego H. Milone, L. Forzani
DEXA
2008
Springer
130views Database» more  DEXA 2008»
13 years 6 months ago
Classifying Evolving Data Streams Using Dynamic Streaming Random Forests
We consider the problem of data-stream classification, introducing a stream-classification algorithm, Dynamic Streaming Random Forests, that is able to handle evolving data streams...
Hanady Abdulsalam, David B. Skillicorn, Patrick Ma...