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» Situation Recognition: Representation and Algorithms
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ICDM
2008
IEEE
109views Data Mining» more  ICDM 2008»
14 years 3 months ago
Learning by Propagability
In this paper, we present a novel feature extraction framework, called learning by propagability. The whole learning process is driven by the philosophy that the data labels and o...
Bingbing Ni, Shuicheng Yan, Ashraf A. Kassim, Loon...
DAS
2008
Springer
13 years 10 months ago
On the Reading of Tables of Contents
This paper presents a framework for understanding tables of contents (TOC) of books, journals, and magazines. We propose a universal logical structure representation in terms of a...
Prateek Sarkar, Eric Saund
3DPVT
2006
IEEE
247views Visualization» more  3DPVT 2006»
14 years 2 months ago
Automatic 3D Face Detection, Normalization and Recognition
A fully automatic 3D face recognition algorithm is presented. Several novelties are introduced to make the recognition robust to facial expressions and efficient. These novelties...
Ajmal S. Mian, Mohammed Bennamoun, Robyn A. Owens
ATAL
2006
Springer
14 years 16 days ago
Rule value reinforcement learning for cognitive agents
RVRL (Rule Value Reinforcement Learning) is a new algorithm which extends an existing learning framework that models the environment of a situated agent using a probabilistic rule...
Christopher Child, Kostas Stathis
PR
2008
178views more  PR 2008»
13 years 7 months ago
An effective and fast iris recognition system based on a combined multiscale feature extraction technique
The randomness of iris pattern makes it one of the most reliable biometric traits. On the other hand, the complex iris image structure and the various sources of intra-class varia...
Makram Nabti, Ahmed Bouridane