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ICCV
2009
IEEE
1556views Computer Vision» more  ICCV 2009»
16 years 2 months ago
Kernel Methods for Weakly Supervised Mean Shift Clustering
Mean shift clustering is a powerful unsupervised data analysis technique which does not require prior knowledge of the number of clusters, and does not constrain the shape of th...
Oncel Tuzel, Fatih Porikli, Peter Meer
ICIP
2008
IEEE
15 years 11 months ago
Supervised image segmentation via ground truth decomposition
This paper proposes a data driven image segmentation algorithm, based on decomposing the target output (ground truth). Classical pixel labeling methods utilize machine learning al...
Ilya Levner, Russell Greiner, Hong Zhang
CVPR
2009
IEEE
15 years 4 months ago
Automatic facial landmark labeling with minimal supervision
Landmark labeling of training images is essential for many learning tasks in computer vision, such as object detection, tracking, and alignment. Image labeling is typically conduc...
Yan Tong, Xiaoming Liu 0002, Frederick W. Wheeler,...
HICSS
2005
IEEE
117views Biometrics» more  HICSS 2005»
15 years 3 months ago
Movie Review Mining: a Comparison between Supervised and Unsupervised Classification Approaches
Web content mining is intended to help people discover valuable information from large amount of unstructured data on the web. Movie review mining classifies movie reviews into tw...
Pimwadee Chaovalit, Lina Zhou
ACL
2008
14 years 11 months ago
Semi-Supervised Sequential Labeling and Segmentation Using Giga-Word Scale Unlabeled Data
This paper provides evidence that the use of more unlabeled data in semi-supervised learning can improve the performance of Natural Language Processing (NLP) tasks, such as part-o...
Jun Suzuki, Hideki Isozaki