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» Segmentation of medical images using a genetic algorithm
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CIVR
2005
Springer
123views Image Analysis» more  CIVR 2005»
16 years 8 days ago
Region-Based Image Clustering and Retrieval Using Multiple Instance Learning
Multiple Instance Learning (MIL) is a special kind of supervised learning problem that has been studied actively in recent years. We propose an approach based on One-Class Support ...
Chengcui Zhang, Xin Chen
TIP
2010
94views more  TIP 2010»
15 years 1 months ago
User-Friendly Interactive Image Segmentation Through Unified Combinatorial User Inputs
One weakness in the existing interactive image segmentation algorithms is the lack of more intelligent ways to understand the intention of user inputs. In this paper, we advocate t...
Wenxian Yang, Jianfei Cai, Jianmin Zheng, Jiebo Lu...
ECCV
2008
Springer
16 years 8 months ago
Weakly Supervised Object Localization with Stable Segmentations
Multiple Instance Learning (MIL) provides a framework for training a discriminative classifier from data with ambiguous labels. This framework is well suited for the task of learni...
Carolina Galleguillos, Boris Babenko, Andrew Rabin...
JMIV
2007
145views more  JMIV 2007»
15 years 6 months ago
Level Lines Selection with Variational Models for Segmentation and Encoding
Abstract. This paper discusses the interest of the Tree of Shapes of an image as a region oriented image representation. The Tree of Shapes offers a compact and structured represen...
Coloma Ballester, Vicent Caselles, Laura Igual, Ll...
PAMI
1998
124views more  PAMI 1998»
15 years 6 months ago
Robust Adaptive Segmentation of Range Images
—We propose a novel image segmentation technique using the robust, adaptive least kth order squares (ALKS) estimator which minimizes the kth order statistics of the squared of re...
Kil-Moo Lee, Peter Meer, Rae-Hong Park