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

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References in zbMATH (referenced in 25 articles )

Showing results 1 to 20 of 25.
Sorted by year (citations)

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  1. 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
  2. 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
  3. Martí Bosch: DetecTree: Tree detection from aerial imagery in Python (2020) not zbMATH
  4. Picella, F.; Robinet, J.-Ch.; Cherubini, S.: On the influence of the modelling of superhydrophobic surfaces on laminar-turbulent transition (2020)
  5. Ruman Gerst; Anna Medyukhina; Marc Thilo Figge: MISA++: A standardized interface for automated bioimage analysis (2020) not zbMATH
  6. Shizuo Kaji, Takeki Sudo, Kazushi Ahara: Cubical Ripser: Software for computing persistent homology of image and volume data (2020) arXiv
  7. 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)
  8. Castro, Daniel C.; Tan, Jeremy; Kainz, Bernhard; Konukoglu, Ender; Glocker, Ben: Morpho-MNIST: quantitative assessment and diagnostics for representation learning (2019)
  9. Edgar Riba, Dmytro Mishkin, Daniel Ponsa, Ethan Rublee, Gary Bradski: Kornia: an Open Source Differentiable Computer Vision Library for PyTorch (2019) arXiv
  10. Eric W. Koch, Ryan D. Boyden, Blakesley Burkhart, Adam Ginsburg, Jason L. Loeppky, Stella S.R. Offner: TurbuStat: Turbulence Statistics in Python (2019) arXiv
  11. 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
  12. 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
  13. Huan, Er-Yang; Wen, Gui-Hua: Multilevel and multiscale feature aggregation in deep networks for facial constitution classification (2019)
  14. Philipp S. Sommer; Dilan Rech; Manuel Chevalier; Basil A. S.Davis: straditize: Digitizing stratigraphic diagrams (2019) not zbMATH
  15. Potter, Samuel F.; Cameron, Maria K.: Ordered line integral methods for solving the eikonal equation (2019)
  16. Joseph C. Ferguson, Francesco Panerai, Arnaud Borner, Nagi N. Mansour: PuMA: the Porous Microstructure Analysis software (2018) not zbMATH
  17. Lakatos, Dóra; Somfai, Ellák; Méhes, Elod; Czirók, András: Soluble VEGFR1 signaling guides vascular patterns into dense branching morphologies (2018)
  18. Schreiber, Jacob: pomegranate: fast and flexible probabilistic modeling in Python (2018)
  19. Völgyes, David; Martinsen, Anne Catrine Trægde; Stray-Pedersen, Arne; Waaler, Dag; Pedersen, Marius: A weighted histogram-based tone mapping algorithm for CT images (2018)
  20. Antil, Harbir; Bartels, Sören: Spectral approximation of fractional PDEs in image processing and phase field modeling (2017)

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