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» Meta-Evaluation of Image Segmentation Using Machine Learning
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KDD
2012
ACM
205views Data Mining» more  KDD 2012»
11 years 10 months ago
Rank-loss support instance machines for MIML instance annotation
Multi-instance multi-label learning (MIML) is a framework for supervised classification where the objects to be classified are bags of instances associated with multiple labels....
Forrest Briggs, Xiaoli Z. Fern, Raviv Raich
MICCAI
2006
Springer
14 years 8 months ago
A General Framework for Image Segmentation Using Ordered Spatial Dependency
The segmentation problem appears in most medical imaging applications. Many research groups are pushing toward a whole body segmentation based on atlases. With a similar objective,...
Mikaël Rousson, Chenyang Xu
ICASSP
2009
IEEE
13 years 11 months ago
High-level feature extraction using SVM with walk-based graph kernel
We investigate a method using support vector machines (SVMs) with walk-based graph kernels for high-level feature extraction from images. In this method, each image is first segme...
Jean-Philippe Vert, Tomoko Matsui, Shin'ichi Satoh...
PREMI
2005
Springer
14 years 28 days ago
Learning to Segment Document Images
A hierarchical framework for document segmentation is proposed as an optimization problem. The model incorporates the dependencies between various levels of the hierarchy unlike tr...
K. S. Sesh Kumar, Anoop M. Namboodiri, C. V. Jawah...
VIP
2003
13 years 8 months ago
Optimal Selection of Image Segmentation Algorithms Based on Performance Prediction
Using different algorithms to segment different images is a quite straightforward strategy for automated image segmentation. But the difficulty of the optimal algorithm selection ...
Yong Xia, David Dagan Feng, Rongchun Zhao