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CVPR
2012
IEEE
13 years 6 months ago
Geometry constrained sparse coding for single image super-resolution
The choice of the over-complete dictionary that sparsely represents data is of prime importance for sparse codingbased image super-resolution. Sparse coding is a typical unsupervi...
Xiaoqiang Lu, Haoliang Yuan, Pingkun Yan, Yuan Yua...
130
Voted
MICCAI
2006
Springer
16 years 4 months ago
Multi-resolution Vessel Segmentation Using Normalized Cuts in Retinal Images
Abstract. Retinal vessel segmentation is an essential step of the diagnoses of various eye diseases. In this paper, we propose an automatic, efficient and unsupervised method based...
Wenchao Cai, Albert C. S. Chung
131
Voted
PCM
2005
Springer
157views Multimedia» more  PCM 2005»
15 years 9 months ago
Segmentation of the Liver Using the Deformable Contour Method on CT Images
Abstract. Automatic liver segmentation from abdominal computed tomography (CT) images is one of the most important steps for computeraided diagnosis (CAD) for liver CT. However, th...
Seong-Jae Lim, Yong-Yeon Jeong, Yo-Sung Ho
144
Voted
DAGM
2010
Springer
15 years 3 months ago
Semi-supervised Learning of Edge Filters for Volumetric Image Segmentation
Abstract. For every segmentation task, prior knowledge about the object that shall be segmented has to be incorporated. This is typically performed either automatically by using la...
Margret Keuper, Robert Bensch, Karsten Voigt, Alex...
129
Voted
ICDAR
2007
IEEE
15 years 10 months ago
A Sparse and Locally Shift Invariant Feature Extractor Applied to Document Images
We describe an unsupervised learning algorithm for extracting sparse and locally shift-invariant features. We also devise a principled procedure for learning hierarchies of invari...
Marc'Aurelio Ranzato, Yann LeCun