Sciweavers

ICPR
2008
IEEE
13 years 10 months ago
RANSAC-SVM for large-scale datasets
Support Vector Machines (SVMs), though accurate, are still difficult to solve large-scale applications, due to the computational and storage requirement. To relieve this problem,...
Kenji Watanabe, Takio Kurita
IAT
2009
IEEE
13 years 10 months ago
An Intelligent Agent That Autonomously Learns How to Translate
—We describe the design of an autonomous agent that can teach itself how to translate from a foreign language, by first assembling its own training set, then using it to improve...
Marco Turchi, Tijl De Bie, Nello Cristianini
CVPR
2010
IEEE
13 years 11 months ago
Context-Constrained Hallucination for Image Super-Resolution
This paper proposes a context-constrained hallucination approach for image super-resolution. Through building a training set of high-resolution/low-resolution image segment pairs,...
Jian Sun, Jiejie Zhu, Marshall Tappen
ISBI
2008
IEEE
14 years 4 months ago
Landmark selection for shape model construction via equalization of variance
Model-based segmentation approaches, such as those employing Active Shape Models (ASMs), have proved to be useful for medical image segmentation and understanding. To build the mo...
Sylvia Rueda, Jayaram K. Udupa, Li Bai
ICIP
2002
IEEE
14 years 5 months ago
Optimal face reconstruction using training
In previous work [2] we considered the problem of image interpolation from an adaptive optimal recovery point of view. We showed how a training set S determines a quadratic signal...
D. Darian Muresan, Thomas W. Parks
ICIP
2005
IEEE
14 years 5 months ago
Layered local prediction network with dynamic learning for face super-resolution
In this paper, we propose a novel framework for face super-resolution based on a layered predictor network. In the first layer, multiple predictors are trained online with a dynami...
Dahua Lin, Wei Liu, Xiaoou Tang
ECCV
2002
Springer
14 years 5 months ago
3D Statistical Shape Models Using Direct Optimisation of Description Length
We describe an automatic method for building optimal 3D statistical shape models from sets of training shapes. Although shape models show considerable promise as a basis for segmen...
Rhodri H. Davies, Carole J. Twining, Timothy F. Co...
ICCV
2007
IEEE
14 years 5 months ago
An Empirical Study of Object Category Recognition: Sequential Testing with Generalized Samples
In this paper we present an empirical study of object category recognition using generalized samples and a set of sequential tests. We study 33 categories, each consisting of a sm...
Liang Lin, Shaowu Peng, Jake Porway, Song Chun Zhu...