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» On the robust detection of edges in time series filtering
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ICDM
2009
IEEE
150views Data Mining» more  ICDM 2009»
13 years 5 months ago
Filtering and Refinement: A Two-Stage Approach for Efficient and Effective Anomaly Detection
Anomaly detection is an important data mining task. Most existing methods treat anomalies as inconsistencies and spend the majority amount of time on modeling normal instances. A r...
Xiao Yu, Lu An Tang, Jiawei Han
ACCV
2010
Springer
13 years 2 months ago
Automatic Workflow Monitoring in Industrial Environments
Robust automatic workflow monitoring using visual sensors in industrial environments is still an unsolved problem. This is mainly due to the difficulties of recording data in work ...
Galina V. Veres, Helmut Grabner, Lee Middleton, Lu...
ECML
2007
Springer
14 years 1 months ago
Learning an Outlier-Robust Kalman Filter
We introduce a modified Kalman filter that performs robust, real-time outlier detection, without the need for manual parameter tuning by the user. Systems that rely on high quali...
Jo-Anne Ting, Evangelos Theodorou, Stefan Schaal
ICIP
1998
IEEE
14 years 9 months ago
EXM Eigen Templates for Detecting and Classifying Arbitrary Junctions
A novel method for extracting parametric junction and corner features in images is presented. By treating each complex feature as a combination of elementary line and edge feature...
Dibyendu Nandy, Jezekiel Ben-Arie
MICCAI
2005
Springer
14 years 8 months ago
Support Vector Clustering for Brain Activation Detection
In this paper, we propose a new approach to detect activated time series in functional MRI using support vector clustering (SVC). We extract Fourier coefficients as the features of...
Defeng Wang, Lin Shi, Daniel S. Yeung, Pheng-Ann H...