Semi-supervised Learning for Large Scale Image Cosegmentation

This paper introduces to use semi-supervised learning for large scale image co segmentation. Different from traditional unsupervised co segmentation that does not use any segmentation ground truth, semi-supervised co segmentation exploits the similarity from both the very limited training image fore...

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Bibliographic Details
Published in:	2013 IEEE International Conference on Computer Vision pp. 393 - 400
Main Authors:	Wang, Zhengxiang, Liu, Rujie
Format:	Conference Proceeding Journal Article
Language:	English
Published:	IEEE 01.12.2013
Subjects:	Binary quadratic programming problem Computer vision Energy conservation Energy management Energy minimization function Ground truth Histograms Image cosegmentation Image segmentation Iterative algorithms Mathematical analysis Mathematical models Minimization Quadratic programming Segmentation Segments Semi-supervised learning Semisupervised learning Training Training data Vectors
ISSN:	1550-5499
Online Access:	Get full text
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