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» Learning the Relative Importance of Features in Image Data
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CVPR
2003
IEEE
16 years 6 months ago
An Efficient Approach to Learning Inhomogeneous Gibbs Model
Inhomogeneous Gibbs model (IGM) [4] is an effective maximum entropy model in characterizing complex highdimensional distributions. However, its training process is so slow that th...
Ziqiang Liu, Hong Chen, Heung-Yeung Shum
ICML
2006
IEEE
16 years 4 months ago
Learning a kernel function for classification with small training samples
When given a small sample, we show that classification with SVM can be considerably enhanced by using a kernel function learned from the training data prior to discrimination. Thi...
Tomer Hertz, Aharon Bar-Hillel, Daphna Weinshall
182
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IFIP
2005
Springer
15 years 9 months ago
Content-Based Image Retrieval for Digital Forensics
Digital forensic investigators are often faced with the task of manually examining a large number of (photographic) images in order to identify potential evidence. The task can be...
Yixin Chen, Vassil Roussev, Golden G. Richard III,...
DAS
2004
Springer
15 years 9 months ago
Automatic Fax Routing
Abstract. We present a system for automatic FAX routing which processes incoming FAX images and forwards them to the correct email alias. The system first performs optical charact...
Paul A. Viola, James Rinker, Martin Law
CVPR
2008
IEEE
16 years 6 months ago
Boosted deformable model for human body alignment
This paper studies image alignment, the problem of learning a shape and appearance model from labeled data and efficiently fitting the model to a non-rigid object with large varia...
Xiaoming Liu 0002, Ting Yu, Thomas Sebastian, Pete...