scikit-image

Scikit-image: image processing in python. scikit-image is a collection of algorithms for image processing. It is available free of charge and free of restriction.

Keywords for this software

Anything in here will be replaced on browsers that support the canvas element

References in zbMATH (referenced in 31 articles )

Showing results 1 to 20 of 31.
Sorted by year (citations)

1 2 next

  1. Alex M. Ganose; Amy Searle; Anubhav Jain; Sinéad M. Griffin: IFermi: A python library for Fermi surface generation and analysis (2021) not zbMATH
  2. Emzir, Muhammad; Lasanen, Sari; Purisha, Zenith; Roininen, Lassi; Särkkä, Simo: Non-stationary multi-layered Gaussian priors for Bayesian inversion (2021)
  3. Haan, Sebastian: GeoBO: Python package for Multi-Objective Bayesian Optimisation and Joint Inversion in Geosciences (2021) not zbMATH
  4. Jon Schwenk; Jayaram Hariharan: RivGraph: Automatic extraction and analysis of river and delta channel network topology (2021) not zbMATH
  5. Michael Julian Orella, McLain Evan Leonard, Yuriy Román-Leshkov, Fikile Richard Brushett: High-throughput analysis of contact angle goniometry data using DropPy (2021) not zbMATH
  6. Qiusheng Wu: lidar: A Python package for delineating nested surface depressions from digital elevation data (2021) not zbMATH
  7. Zoltan Csati, Jean-François Witz, Vincent Magnier, Ahmed El Bartali, Nathalie Limodin; Denis Najjar: CristalX: Facilitating simulations for experimentally obtained grain-based microstructures (2021) not zbMATH
  8. Alain Jungo, Olivier Scheidegger, Mauricio Reyes, Fabian Balsiger: pymia: A Python package for data handling and evaluation in deep learning-based medical image analysis (2020) arXiv
  9. Leonardo Uieda; Santiago Rubén Soler; Rémi Rampin; Hugo van Kemenade; Matthew Turk; Daniel Shapero; Anderson Banihirwe; John Leeman: Pooch: A friend to fetch your data files (2020) not zbMATH
  10. Martí Bosch: DetecTree: Tree detection from aerial imagery in Python (2020) not zbMATH
  11. Picella, F.; Robinet, J.-Ch.; Cherubini, S.: On the influence of the modelling of superhydrophobic surfaces on laminar-turbulent transition (2020)
  12. Ruman Gerst; Anna Medyukhina; Marc Thilo Figge: MISA++: A standardized interface for automated bioimage analysis (2020) not zbMATH
  13. Shizuo Kaji, Takeki Sudo, Kazushi Ahara: Cubical Ripser: Software for computing persistent homology of image and volume data (2020) arXiv
  14. Berghout, Pieter; Zhu, Xiaojue; Chung, Daniel; Verzicco, Roberto; Stevens, Richard J. A. M.; Lohse, Detlef: Direct numerical simulations of Taylor-Couette turbulence: the effects of sand grain roughness (2019)
  15. Castro, Daniel C.; Tan, Jeremy; Kainz, Bernhard; Konukoglu, Ender; Glocker, Ben: Morpho-MNIST: quantitative assessment and diagnostics for representation learning (2019)
  16. Edgar Riba, Dmytro Mishkin, Daniel Ponsa, Ethan Rublee, Gary Bradski: Kornia: an Open Source Differentiable Computer Vision Library for PyTorch (2019) arXiv
  17. Eric W. Koch, Ryan D. Boyden, Blakesley Burkhart, Adam Ginsburg, Jason L. Loeppky, Stella S.R. Offner: TurbuStat: Turbulence Statistics in Python (2019) arXiv
  18. Gostick J, Khan ZA, Tranter TG, Kok MDR, Agnaou M, Sadeghi MA, Jervis R.: PoreSpy: A Python Toolkit for Quantitative Analysis of Porous Media Images (2019) not zbMATH
  19. Hsieh-Fu Tsai, Joanna Gajda, Tyler F.W. Sloan, Andrei Rares, Jason Ting-Chun Chou, Amy Q. Shen: Usiigaci: Instance-aware cell tracking in stain-free phase contrast microscopy enabled by machine learning (2019) not zbMATH
  20. Huan, Er-Yang; Wen, Gui-Hua: Multilevel and multiscale feature aggregation in deep networks for facial constitution classification (2019)

1 2 next