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CVPR
2011
IEEE
12 years 9 months ago
Kernelized Structural SVM Learning for Supervised Object Segmentation
Object segmentation needs to be driven by top-down knowledge to produce semantically meaningful results. In this paper, we propose a supervised segmentation approach that tightly ...
Luca Bertelli, Tianli Yu, Diem Vu, Salih Gokturk
DAGM
2010
Springer
13 years 5 months ago
Incremental Learning in the Energy Minimisation Framework for Interactive Segmentation
In this article we propose a method for parameter learning within the energy minimisation framework for segmentation. We do this in an incremental way where user input is required ...
Denis Kirmizigül, Dmitrij Schlesinger
PAMI
2006
138views more  PAMI 2006»
13 years 5 months ago
Context-Based Segmentation of Image Sequences
We describe an algorithm for context-based segmentation of visual data. New frames in an image sequence (video) are segmented based on the prior segmentation of earlier frames in ...
Jacob Goldberger, Hayit Greenspan
IJCNN
2006
IEEE
13 years 11 months ago
Learning to Segment Any Random Vector
— We propose a method that takes observations of a random vector as input, and learns to segment each observation into two disjoint parts. We show how to use the internal coheren...
Aapo Hyvärinen, Jukka Perkiö
ICPR
2000
IEEE
13 years 9 months ago
Handwritten Character Segmentation Using Transformation-Based Learning
This paper presents a character segmentation algorithm for unconstrained cursive handwritten text. The transformation-based learning method and a simplified variation of it are us...
Ergina Kavallieratou, Efstathios Stamatatos, Nikos...