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» A New Multiple Kernel Approach for Visual Concept Learning
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ICCV
2009
IEEE
1824views Computer Vision» more  ICCV 2009»
15 years 2 months ago
Beyond the Euclidean distance: Creating effective visual codebooks using the histogram intersection kernel
Common visual codebook generation methods used in a Bag of Visual words model, e.g. k-means or Gaussian Mixture Model, use the Euclidean distance to cluster features into visual...
Jianxin Wu, James M. Rehg
ECTEL
2006
Springer
14 years 1 months ago
Blended Learning Concepts - a Short Overview
This paper presents a short overview of blended learning, showing arguments for and against these concepts. Potential blended learning scenarios are described that vary depending o...
Sonja Trapp
CVPR
2007
IEEE
14 years 11 months ago
Concurrent Multiple Instance Learning for Image Categorization
We propose a new multiple instance learning (MIL) algorithm to learn image categories. Unlike existing MIL algorithms, in which the individual instances in a bag are assumed to be...
Guo-Jun Qi, Xian-Sheng Hua, Yong Rui, Tao Mei, Jin...
CVPR
2010
IEEE
14 years 6 months ago
Online-Batch Strongly Convex Multi Kernel Learning
Several object categorization algorithms use kernel methods over multiple cues, as they offer a principled approach to combine multiple cues, and to obtain state-of-theart perform...
Francesco Orabona, Jie Luo, Barbara Caputo
SDM
2007
SIAM
176views Data Mining» more  SDM 2007»
13 years 11 months ago
Adaptive Concept Learning through Clustering and Aggregation of Relational Data
We introduce a new approach for Clustering and Aggregating Relational Data (CARD). We assume that data is available in a relational form, where we only have information about the ...
Hichem Frigui, Cheul Hwang