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» Robustness of Classifiers to Changing Environments
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AROBOTS
2010
128views more  AROBOTS 2010»
13 years 6 months ago
Track-based self-supervised classification of dynamic obstacles
Abstract This work introduces a self-supervised architecture for robust classification of moving obstacles in urban environments. Our approach presents a hierarchical scheme that r...
Roman Katz, Juan Nieto, Eduardo Mario Nebot, Bertr...
ICIP
2005
IEEE
13 years 11 months ago
Robust face alignment based on local texture classifiers
We propose a robust face alignment algorithm with a novel discriminative local texture model. Different from the conventional descriptive PCA local texture model in ASM, classifie...
Li Zhang, Haizhou Ai, Shengjun Xin, Chang Huang, S...
JIPS
2010
159views more  JIPS 2010»
13 years 1 months ago
A Dynamic Approach to Estimate Change Impact using Type of Change Propagation
Software evolution is an ongoing process carried out with the aim of extending base applications either for adding new functionalities or for adapting software to changing environm...
Chetna Gupta, Yogesh Singh, Durg Singh Chauhan
TNN
2008
124views more  TNN 2008»
13 years 6 months ago
Just-in-Time Adaptive Classifiers - Part II: Designing the Classifier
Aging effects, environmental changes, thermal drifts, and soft and hard faults affect physical systems by changing their nature and behavior over time. To cope with a process evolu...
Cesare Alippi, Manuel Roveri
ECCV
2006
Springer
13 years 8 months ago
Robust Face Alignment Based on Hierarchical Classifier Network
Abstract. Robust face alignment is crucial for many face processing applications. As face detection only gives a rough estimation of face region, one important problem is how to al...
Li Zhang, Haizhou Ai, Shihong Lao