Energy Minimization Methods in Computer Vision and Pattern Recognition 9th International Conference, EMMCVPR 2013, Lund, Sweden, August 19-21, 2013. Proceedings /
Autres auteurs :
Heyden, Anders.
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editor.
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Kahl, Fredrik.
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editor.
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Olsson, Carl.
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editor.
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Oskarsson, Magnus.
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editor.
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Tai, Xue-Cheng.
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editor.
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SpringerLink (Online service)
Collection :
Lecture Notes in Computer Science,
0302-9743 ;
. 8081
Détails physiques : XII, 363 p. 130 illus. online resource.
ISBN :9783642403958.
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Kahl, Fredrik.
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editor.
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Olsson, Carl.
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editor.
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Oskarsson, Magnus.
--
editor.
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Tai, Xue-Cheng.
--
editor.
|
SpringerLink (Online service)
Sujet(s) :
Computer science.
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Computer software
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Reusability.
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Algorithms.
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Data mining.
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Computer graphics.
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Image processing.
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Pattern recognition.
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Computer Science.
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Pattern Recognition.
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Performance and Reliability.
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Image Processing and Computer Vision.
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Algorithm Analysis and Problem Complexity.
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Computer Imaging, Vision, Pattern Recognition and Graphics.
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Data Mining and Knowledge Discovery.
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Computer software
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Reusability.
|
Algorithms.
|
Data mining.
|
Computer graphics.
|
Image processing.
|
Pattern recognition.
|
Computer Science.
|
Pattern Recognition.
|
Performance and Reliability.
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Image Processing and Computer Vision.
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Algorithm Analysis and Problem Complexity.
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Computer Imaging, Vision, Pattern Recognition and Graphics.
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Data Mining and Knowledge Discovery.
Ressources en ligne :
Exemplaires : http://dx.doi.org/10.1007/978-3-642-40395-8
Medical Imaging -- Image Editing -- 3D Reconstruction -- Shape Matching -- Scene Understanding -- Segmentation; Superpixels -- Statistical Methods and Learning.
This volume constitutes the refereed proceedings of the 9th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2013, held in Lund, Sweden, in August 2013. The 26 revised full papers were carefully reviewed and selected from 40 submissions. The papers are organized in topical sections on Medical Imaging; Image Editing; 3D Reconstruction; Shape Matching; Scene Understanding; Segmentation; Superpixels; Statistical Methods and Learning.
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