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BLISS
2009
IEEE
14 years 10 months ago
Recognition of Dynamic Texture Patterns Using CHLAC Features
In this paper, we propose a statistical scheme for recognizing three-dimensional textures shown in motion images, which we call dynamic textures. The texture characteristics emerg...
Takumi Kobayashi, Tetsuya Higuchi, Tsuneharu Miyaj...
AMFG
2007
IEEE
315views Biometrics» more  AMFG 2007»
15 years 3 months ago
Structured Ordinal Features for Appearance-Based Object Representation
In this paper, we propose a novel appearance-based representation, called Structured Ordinal Feature (SOF). SOF is a binary string encoded by combining eight ordinal blocks in a ci...
ShengCai Liao, Zhen Lei, Stan Z. Li, Xiaotong Yuan...
KDD
1997
ACM
109views Data Mining» more  KDD 1997»
15 years 1 months ago
Beyond Concise and Colorful: Learning Intelligible Rules
A variety of techniques from statistics, signal processing, pattern recognition, machine learning, and neural networks have been proposed to understand data by discovering useful ...
Michael J. Pazzani, Subramani Mani, William Rodman...
ICAPR
2009
Springer
14 years 7 months ago
Online Improved Eigen Tracking
We present a novel predictive statistical framework to improve the performance of an Eigen Tracker which uses fast and efficient eigen space updates to learn new views of the obje...
Subarna Tripathi, Santanu Chaudhury, Sumantra Dutt...
82
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MCS
2009
Springer
15 years 2 months ago
Incremental Learning of Variable Rate Concept Drift
We have recently introduced an incremental learning algorithm, Learn++ .NSE, for Non-Stationary Environments, where the data distribution changes over time due to concept drift. Le...
Ryan Elwell, Robi Polikar