Democratized image analytics by visual programming through integration of deep models and small-scale machine learning
Deep learning approaches for image preprocessing and analysis offer important advantages, but these are rarely incorporated into user-friendly software. Here the authors present an easy-to-use visual programming toolbox integrating deep-learning and interactive data visualization for image analysis.
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Nature Portfolio
2019
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oai:doaj.org-article:8fe78876de9a43e59a6f2f0dc33ed1f82021-12-02T17:01:29ZDemocratized image analytics by visual programming through integration of deep models and small-scale machine learning10.1038/s41467-019-12397-x2041-1723https://doaj.org/article/8fe78876de9a43e59a6f2f0dc33ed1f82019-10-01T00:00:00Zhttps://doi.org/10.1038/s41467-019-12397-xhttps://doaj.org/toc/2041-1723Deep learning approaches for image preprocessing and analysis offer important advantages, but these are rarely incorporated into user-friendly software. Here the authors present an easy-to-use visual programming toolbox integrating deep-learning and interactive data visualization for image analysis.Primož GodecMatjaž PančurNejc IleničAndrej ČoparMartin StražarAleš ErjavecAjda PretnarJanez DemšarAnže StaričMarko ToplakLan ŽagarJan HartmanHamilton WangRiccardo BellazziUroš PetrovičSilvia GaragnaMaurizio ZuccottiDongsu ParkGad ShaulskyBlaž ZupanNature PortfolioarticleScienceQENNature Communications, Vol 10, Iss 1, Pp 1-7 (2019) |
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DOAJ |
| collection |
DOAJ |
| language |
EN |
| topic |
Science Q |
| spellingShingle |
Science Q Primož Godec Matjaž Pančur Nejc Ilenič Andrej Čopar Martin Stražar Aleš Erjavec Ajda Pretnar Janez Demšar Anže Starič Marko Toplak Lan Žagar Jan Hartman Hamilton Wang Riccardo Bellazzi Uroš Petrovič Silvia Garagna Maurizio Zuccotti Dongsu Park Gad Shaulsky Blaž Zupan Democratized image analytics by visual programming through integration of deep models and small-scale machine learning |
| description |
Deep learning approaches for image preprocessing and analysis offer important advantages, but these are rarely incorporated into user-friendly software. Here the authors present an easy-to-use visual programming toolbox integrating deep-learning and interactive data visualization for image analysis. |
| format |
article |
| author |
Primož Godec Matjaž Pančur Nejc Ilenič Andrej Čopar Martin Stražar Aleš Erjavec Ajda Pretnar Janez Demšar Anže Starič Marko Toplak Lan Žagar Jan Hartman Hamilton Wang Riccardo Bellazzi Uroš Petrovič Silvia Garagna Maurizio Zuccotti Dongsu Park Gad Shaulsky Blaž Zupan |
| author_facet |
Primož Godec Matjaž Pančur Nejc Ilenič Andrej Čopar Martin Stražar Aleš Erjavec Ajda Pretnar Janez Demšar Anže Starič Marko Toplak Lan Žagar Jan Hartman Hamilton Wang Riccardo Bellazzi Uroš Petrovič Silvia Garagna Maurizio Zuccotti Dongsu Park Gad Shaulsky Blaž Zupan |
| author_sort |
Primož Godec |
| title |
Democratized image analytics by visual programming through integration of deep models and small-scale machine learning |
| title_short |
Democratized image analytics by visual programming through integration of deep models and small-scale machine learning |
| title_full |
Democratized image analytics by visual programming through integration of deep models and small-scale machine learning |
| title_fullStr |
Democratized image analytics by visual programming through integration of deep models and small-scale machine learning |
| title_full_unstemmed |
Democratized image analytics by visual programming through integration of deep models and small-scale machine learning |
| title_sort |
democratized image analytics by visual programming through integration of deep models and small-scale machine learning |
| publisher |
Nature Portfolio |
| publishDate |
2019 |
| url |
https://doaj.org/article/8fe78876de9a43e59a6f2f0dc33ed1f8 |
| work_keys_str_mv |
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