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» Learning Models for Object Recognition
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PR
2006
127views more  PR 2006»
13 years 10 months ago
Unsupervised possibilistic clustering
In fuzzy clustering, the fuzzy c-means (FCM) clustering algorithm is the best known and used method. Since the FCM memberships do not always explain the degrees of belonging for t...
Miin-Shen Yang, Kuo-Lung Wu
SIGIR
2008
ACM
13 years 10 months ago
Knowledge transformation from word space to document space
In most IR clustering problems, we directly cluster the documents, working in the document space, using cosine similarity between documents as the similarity measure. In many real...
Tao Li, Chris H. Q. Ding, Yi Zhang 0005, Bo Shao
ECCV
2008
Springer
14 years 12 months ago
Robust 3D Pose Estimation and Efficient 2D Region-Based Segmentation from a 3D Shape Prior
In this work, we present an approach to jointly segment a rigid object in a 2D image and estimate its 3D pose, using the knowledge of a 3D model. We naturally couple the two proces...
Samuel Dambreville, Romeil Sandhu, Anthony J. Yezz...
CVPR
2012
IEEE
12 years 15 days ago
A learning-based framework for depth ordering
Depth ordering is instrumental for understanding the 3D geometry of an image. We as humans are surprisingly good ordering even with abstract 2D line drawings. In this paper we pro...
Zhaoyin Jia, Andrew C. Gallagher, Yao-Jen Chang, T...
BMCBI
2006
137views more  BMCBI 2006»
13 years 10 months ago
A maximum likelihood framework for protein design
Background: The aim of protein design is to predict amino-acid sequences compatible with a given target structure. Traditionally envisioned as a purely thermodynamic question, thi...
Claudia L. Kleinman, Nicolas Rodrigue, Céci...