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» Learning the Relative Importance of Features in Image Data
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KDD
2012
ACM
207views Data Mining» more  KDD 2012»
11 years 11 months ago
Robust multi-task feature learning
Multi-task learning (MTL) aims to improve the performance of multiple related tasks by exploiting the intrinsic relationships among them. Recently, multi-task feature learning alg...
Pinghua Gong, Jieping Ye, Changshui Zhang
DAGM
2008
Springer
13 years 10 months ago
Learning Visual Compound Models from Parallel Image-Text Datasets
Abstract. In this paper, we propose a new approach to learn structured visual compound models from shape-based feature descriptions. We use captioned text in order to drive the pro...
Jan Moringen, Sven Wachsmuth, Sven J. Dickinson, S...
BMVC
1997
13 years 10 months ago
Employing Region Features for Searching an Image Database
This paper describes recent work on the use of regional data extracted from segmented images for use as search keys in an image database query system. The motivation for this work...
Matthew E. J. Wood, Neill W. Campbell, Barry T. Th...
ICCV
2011
IEEE
12 years 8 months ago
Relative Attributes
Human-nameable visual “attributes” can benefit various recognition tasks. However, existing techniques restrict these properties to categorical labels (for example, a person ...
Devi Parikh, Kristen Grauman
COLING
2010
13 years 3 months ago
Improving Name Origin Recognition with Context Features and Unlabelled Data
We demonstrate the use of context features, namely, names of places, and unlabelled data for the detection of personal name language of origin. While some early work used either r...
Vladimir Pervouchine, Min Zhang, Ming Liu, Haizhou...