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CVPR
2009
IEEE
16 years 11 months ago
Let the Kernel Figure it Out; Principled Learning of Pre-processing for Kernel Classifiers
Most modern computer vision systems for high-level tasks, such as image classification, object recognition and segmentation, are based on learning algorithms that are able to se...
Peter V. Gehler, Sebastian Nowozin
CVPR
2001
IEEE
16 years 6 months ago
Learning Probabilistic Distribution Model for Multi-View Face Detection
Modeling subspaces of a distribution of interest in high dimensional spaces is a challenging problem in pattern analysis. In this paper, we present a novel framework for pose inva...
Lie Gu, Stan Z. Li, HongJiang Zhang
PREMI
2007
Springer
15 years 10 months ago
Self Adaptable Recognizer for Document Image Collections
Abstract. This paper presents an architecture that enables the recognizer to learn incrementally and, thereby adapt to document image collections for performance improvement. We ar...
Million Meshesha, C. V. Jawahar
ICML
2003
IEEE
16 years 5 months ago
Linear Programming Boosting for Uneven Datasets
The paper extends the notion of linear programming boosting to handle uneven datasets. Extensive experiments with text classification problem compare the performance of a number o...
Jure Leskovec, John Shawe-Taylor
ECCV
2010
Springer
15 years 9 months ago
Efficient Highly Over-Complete Sparse Coding using a Mixture Model
Sparse coding of sensory data has recently attracted notable attention in research of learning useful features from the unlabeled data. Empirical studies show that mapping the data...