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.
Enregistré dans:
Auteurs principaux: | 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 |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Nature Portfolio
2019
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/8fe78876de9a43e59a6f2f0dc33ed1f8 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Functional and structural phenotyping of cardiomyocytes in the 3D organization of embryoid bodies exposed to arsenic trioxide
par: Paola Rebuzzini, et autres
Publié: (2021) -
Microfluidic control over topological states in channel-confined nematic flows
par: Simon Čopar, et autres
Publié: (2020) -
PERCUTANEOUS ENDOSCOPIC GASTROSTOMY IN CHILDREN: DATA FROM THE CHILDREN‘S HOSPITAL IN LJUBLJANA
par: Tjaša Žagar, et autres
Publié: (2021) -
ENDOSKOPSKA GASTROSTOMA PRI OTROCIH: PODATKI S PEDIATRIČNE KLINIKE V LJUBLJANI
par: Tjaša Žagar, et autres
Publié: (2021) -
Vsebnost ekstraktivov v skorji in lesu robinije (Robinia pseudoacacia L.)
par: Viljem Vek, et autres
Publié: (2019)