Energy Minimization Methods in Computer Vision and Pattern Recognition (eBook, PDF)
10th International Conference, EMMCVPR 2015, Hong Kong, China, January 13-16, 2015. Proceedings Redaktion: Tai, Xue-Cheng; Lysaker, Marius; Chan, Tony F.; Bae, Egil
Energy Minimization Methods in Computer Vision and Pattern Recognition (eBook, PDF)
10th International Conference, EMMCVPR 2015, Hong Kong, China, January 13-16, 2015. Proceedings Redaktion: Tai, Xue-Cheng; Lysaker, Marius; Chan, Tony F.; Bae, Egil
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This volume constitutes the refereed proceedings of the 10th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2015, held in Hong Kong, China, in January 2015. The 36 revised full papers were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on discrete and continuous optimization; image restoration and inpainting; segmentation; PDE and variational methods; motion, tracking and multiview reconstruction; statistical methods and learning; and medical image analysis.
This volume constitutes the refereed proceedings of the 10th International Conference on Energy Minimization Methods in Computer Vision and Pattern Recognition, EMMCVPR 2015, held in Hong Kong, China, in January 2015. The 36 revised full papers were carefully reviewed and selected from 45 submissions. The papers are organized in topical sections on discrete and continuous optimization; image restoration and inpainting; segmentation; PDE and variational methods; motion, tracking and multiview reconstruction; statistical methods and learning; and medical image analysis.
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Inhaltsangabe
Discrete and continuous optimization.- Image restoration and inpainting.- Segmentation.- PDE and variational methods.- Motion, tracking and multiview reconstruction.- Statistical methods and learning.- Medical image analysis.
Discrete and continuous optimization.- Image restoration and inpainting.- Segmentation.- PDE and variational methods.- Motion, tracking and multiview reconstruction.- Statistical methods and learning.- Medical image analysis.
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