References in zbMATH (referenced in 31 articles )

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  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)

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