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» Learning to Recognize Objects with Little Supervision
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NIPS
2007
13 years 6 months ago
Learning Visual Attributes
We present a probabilistic generative model of visual attributes, together with an efficient learning algorithm. Attributes are visual qualities of objects, such as ‘red’, ...
Vittorio Ferrari, Andrew Zisserman
CVPR
2006
IEEE
14 years 6 months ago
Unsupervised Learning of Categories from Sets of Partially Matching Image Features
We present a method to automatically learn object categories from unlabeled images. Each image is represented by an unordered set of local features, and all sets are embedded into...
Kristen Grauman, Trevor Darrell
ECCV
2008
Springer
14 years 6 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...
ICRA
2007
IEEE
117views Robotics» more  ICRA 2007»
13 years 11 months ago
Techniques and Applications for Persistent Backgrounding in a Humanoid Torso Robot
— One of the most basic capabilities for an agent with a vision system is to recognize its own surroundings. Yet surprisingly, despite the ease of doing so, many robots store lit...
David Walker Duhon, Jerod J. Weinman, Erik G. Lear...
LREC
2010
126views Education» more  LREC 2010»
13 years 6 months ago
Predictive Features for Detecting Indefinite Polar Sentences
In recent years, text classification in sentiment analysis has mostly focused on two types of classification, the distinction between objective and subjective text, i.e. subjectiv...
Michael Wiegand, Dietrich Klakow