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GECCO
2006
Springer
177views Optimization» more  GECCO 2006»
13 years 11 months ago
Hyper-ellipsoidal conditions in XCS: rotation, linear approximation, and solution structure
The learning classifier system XCS is an iterative rulelearning system that evolves rule structures based on gradient-based prediction and rule quality estimates. Besides classifi...
Martin V. Butz, Pier Luca Lanzi, Stewart W. Wilson
IROS
2006
IEEE
247views Robotics» more  IROS 2006»
14 years 1 months ago
Towards Open-Ended 3D Rotation and Shift Invariant Object Detection for Robot Companions
- Robot companions need to be able to constantly acquire knowledge about new objects for instance in order to detect them in the environment. This ability is necessary since it is ...
Jens Kubacki, Winfried Baum
ICML
2006
IEEE
14 years 8 months ago
R1-PCA: rotational invariant L1-norm principal component analysis for robust subspace factorization
Principal component analysis (PCA) minimizes the sum of squared errors (L2-norm) and is sensitive to the presence of outliers. We propose a rotational invariant L1-norm PCA (R1-PC...
Chris H. Q. Ding, Ding Zhou, Xiaofeng He, Hongyuan...
PAMI
2007
161views more  PAMI 2007»
13 years 6 months ago
High-Performance Rotation Invariant Multiview Face Detection
Abstract—Rotation invariant multiview face detection (MVFD) aims to detect faces with arbitrary rotation-in-plane (RIP) and rotationoff-plane (ROP) angles in still images or vide...
Chang Huang, Haizhou Ai, Yuan Li, Shihong Lao
IJON
2010
150views more  IJON 2010»
13 years 5 months ago
Linear discriminant analysis using rotational invariant L1 norm
Linear Discriminant Analysis (LDA) is a well-known scheme for supervised subspace learning. It has been widely used in the applications of computer vision and pattern recognition....
Xi Li, Weiming Hu, Hanzi Wang, Zhongfei Zhang