Sciweavers

ICPR
2000
IEEE
14 years 3 months ago
Feature Learning for Recognition with Bayesian Networks
Many realistic visual recognition tasks are “open” in the sense that the number and nature of the categories to be learned are not initially known, and there is no closed set ...
Justus H. Piater, Roderic A. Grupen
CVPR
2010
IEEE
14 years 8 months ago
Exploring Features in a Bayesian Framework for Material Recognition
We are interested in identifying the material category, e.g. glass, metal, fabric, plastic or wood, from a single image of a surface. Unlike other visual recognition tasks in comp...
Ce Liu, Lavanya Sharan, Edward Adelson, Ruth Rosen...
ECCV
2002
Springer
15 years 1 months ago
A Tale of Two Classifiers: SNoW vs. SVM in Visual Recognition
Numerous statistical learning methods have been developed for visual recognition tasks. Few attempts, however, have been made to address theoretical issues, and in particular, stud...
Ming-Hsuan Yang, Dan Roth, Narendra Ahuja
ECCV
2008
Springer
15 years 1 months ago
Training Hierarchical Feed-Forward Visual Recognition Models Using Transfer Learning from Pseudo-Tasks
Abstract. Building visual recognition models that adapt across different domains is a challenging task for computer vision. While feature-learning machines in the form of hierarchi...
Amr Ahmed, Kai Yu, Wei Xu, Yihong Gong, Eric P. Xi...