Cited by 92Medical Image Segmentation TechniquesImage and Signal Denoising MethodsAdvanced Vision and Imaging

Generalized Gradients: Priors on Minimization Flows

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Charpiat, G., Maurel, P., Pons, J.-P., Keriven, R., Faugeras, O.·2007·International Journal of Computer Vision

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Crossref · 10.1007/s11263-006-9966-2

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44 of 44 references verified0 citation errors · 0 not checkable

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  • Our investigation is conceptually motivated by Charpiat et al. [8], who showed that modifying the inner product space for gradient computation can introduce priors that yield smoother optimization paths.

    “Our investigation is conceptually motivated by Charpiat et al. [8], who showed that modifying the inner product space for gradient computation can introduce priors that yield smoother optimization paths.”

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Authors
Charpiat, G., Maurel, P., Pons, J.-P., Keriven, R., & Faugeras, O.
Affiliations
Institut national de recherche en sciences et technologies du numérique (FR)
Corresponding author
Charpiat, G.
Venue
International Journal of Computer Vision
Published
2006-09-14
Volume
73
Issue
3
Pages
325-344
ISSN
  • 0920-5691 (ISSN-L)
  • 1573-1405
OpenAlex
W2027548828
Cited by
91
References
48
Citations by year
2024: 3 · 2023: 2 · 2022: 1 · 2021: 1 · 2020: 2 · 2019: 2 · 2018: 1 · 2017: 7 · 2016: 4 · 2015: 10 · 2014: 6 · 2013: 7 · 2012: 5
FWCI
8.26
Type
journal article
Language
en
Open access
Locations
  • International Journal of Computer Vision (publishedVersion)
  • HAL (submittedVersion, other-oa)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image and Signal Denoising Methods
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Vision and Imaging
Keywords
snakes, gradient flow, generalized gradients, spatial consistency, local minima, sensitivity to initial conditions, image segmentation, variational methods

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