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» Skew Detection via Principal Components Analysis
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ICIP
2005
IEEE
14 years 9 months ago
Eigenwalks: walk detection and biometrics from symmetry patterns
In this paper we present a symmetry-based approach which can be used to detect humans and to extract biometric characteristics from video image-sequences. The method employs a simp...
Laszlo Havasi, Tamás Szirányi, Zolt&...
IBPRIA
2007
Springer
14 years 1 months ago
False Positive Reduction in Breast Mass Detection Using Two-Dimensional PCA
In this paper we present a novel method for reducing false positives in breast mass detection. Our approach is based on using the Two-Dimensional Principal Component Analysis (2DPC...
Arnau Oliver, Xavier Lladó, Joan Mart&iacut...
ACCV
2007
Springer
14 years 1 months ago
Kernel Discriminant Analysis Based on Canonical Differences for Face Recognition in Image Sets
A novel kernel discriminant transformation (KDT) algorithm based on the concept of canonical differences is presented for automatic face recognition applications. For each individu...
Wen-Sheng Vincent Chu, Ju-Chin Chen, Jenn-Jier Jam...
NOMS
2008
IEEE
175views Communications» more  NOMS 2008»
14 years 1 months ago
Analysis of application performance and its change via representative application signatures
Abstract—Application servers are a core component of a multitier architecture that has become the industry standard for building scalable client-server applications. A client com...
Ningfang Mi, Ludmila Cherkasova, Kivanc M. Ozonat,...
SSDBM
2008
IEEE
114views Database» more  SSDBM 2008»
14 years 1 months ago
A General Framework for Increasing the Robustness of PCA-Based Correlation Clustering Algorithms
Abstract. Most correlation clustering algorithms rely on principal component analysis (PCA) as a correlation analysis tool. The correlation of each cluster is learned by applying P...
Hans-Peter Kriegel, Peer Kröger, Erich Schube...