Sciweavers

90 search results - page 2 / 18
» Learning representations for object classification using mul...
Sort
View
CVPR
2012
IEEE
11 years 6 months ago
Unsupervised learning of translation invariant occlusive components
We study unsupervised learning of occluding objects in images of visual scenes. The derived learning algorithm is based on a probabilistic generative model which parameterizes obj...
Zhenwen Dai, Jörg Lücke
CVPR
2007
IEEE
14 years 5 months ago
Filtered Component Analysis to Increase Robustness to Local Minima in Appearance Models
Appearance Models (AM) are commonly used to model appearance and shape variation of objects in images. In particular, they have proven useful to detection, tracking, and synthesis...
Fernando De la Torre, Alvaro Collet, Manuel Quero,...
AI
2005
Springer
13 years 3 months ago
Fast Protein Superfamily Classification Using Principal Component Null Space Analysis
Abstract. The protein family classification problem, which consists of determining the family memberships of given unknown protein sequences, is very important for a biologist for ...
Leon French, Alioune Ngom, Luis Rueda
ICIAR
2004
Springer
13 years 9 months ago
Visual Object Recognition Through One-Class Learning
Abstract. In this paper, several one-class classification methods are investigated in pixel space and PCA (Principal component Analysis) subspace having in mind the need of finding...
QingHua Wang, Luís Seabra Lopes, David M. J...
WWW
2004
ACM
14 years 4 months ago
Ontological representation of learning objects: building interoperable vocabulary and structures
The ontological representation of learning objects is a way to deal with the interoperability and reusability of learning objects (including metadata) through providing a semantic...
Jian Qin, Naybell Hernández