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» Learning Models for Object Recognition
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CVPR
2005
IEEE
16 years 5 months ago
Pruning Training Sets for Learning of Object Categories
Training datasets for learning of object categories are often contaminated or imperfect. We explore an approach to automatically identify examples that are noisy or troublesome fo...
Anelia Angelova, Yaser S. Abu-Mostafa, Pietro Pero...
WACV
2007
IEEE
15 years 9 months ago
Object Categorization Robust to Surface Markings using Entropy-guided Codebook
Visual categorization is fundamentally important for autonomous mobile robots to get intelligence such as novel object acquisition and topological place recognition. The main difï...
Sungho Kim, In-So Kweon
ACL
2012
13 years 5 months ago
Exploiting Social Information in Grounded Language Learning via Grammatical Reduction
This paper uses an unsupervised model of grounded language acquisition to study the role that social cues play in language acquisition. The input to the model consists of (orthogr...
Mark Johnson, Katherine Demuth, Michael C. Frank
ICML
2007
IEEE
16 years 3 months ago
An empirical evaluation of deep architectures on problems with many factors of variation
Recently, several learning algorithms relying on models with deep architectures have been proposed. Though they have demonstrated impressive performance, to date, they have only b...
Hugo Larochelle, Dumitru Erhan, Aaron C. Courville...
ECCV
2008
Springer
16 years 5 months ago
Implementing Decision Trees and Forests on a GPU
We describe a method for implementing the evaluation and training of decision trees and forests entirely on a GPU, and show how this method can be used in the context of object rec...
Toby Sharp