A Probabilistic Associative Model for Segmenting Weakly Supervised Images

Weakly supervised image segmentation is an important yet challenging task in image processing and pattern recognition fields. It is defined as: in the training stage, semantic labels are only at the image-level, without regard to their specific object/scene location within the image. Given a test im...

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Veröffentlicht in:	IEEE transactions on image processing Jg. 23; H. 9; S. 4150 - 4159
Hauptverfasser:	Zhang, Luming, Yang, Yi, Gao, Yue, Yu, Yi, Wang, Changbo, Li, Xuelong
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	United States IEEE 01.09.2014 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Algorithms Bayesian analysis Computational modeling Context Image processing Image segmentation Labels Manifolds Mathematical models Networks Optimization Semantics Vectors associations segmentation Probabilistic model weakly-supervised
ISSN:	1057-7149, 1941-0042, 1941-0042
Online-Zugang:	Volltext
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