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.
Saved in:
Main Authors: | 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 |
Language: | EN |
Published: |
Nature Portfolio
2019
|
Subjects: | |
Online Access: | https://doaj.org/article/8fe78876de9a43e59a6f2f0dc33ed1f8 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Functional and structural phenotyping of cardiomyocytes in the 3D organization of embryoid bodies exposed to arsenic trioxide
by: Paola Rebuzzini, et al.
Published: (2021) -
Microfluidic control over topological states in channel-confined nematic flows
by: Simon Čopar, et al.
Published: (2020) -
PERCUTANEOUS ENDOSCOPIC GASTROSTOMY IN CHILDREN: DATA FROM THE CHILDREN‘S HOSPITAL IN LJUBLJANA
by: Tjaša Žagar, et al.
Published: (2021) -
ENDOSKOPSKA GASTROSTOMA PRI OTROCIH: PODATKI S PEDIATRIČNE KLINIKE V LJUBLJANI
by: Tjaša Žagar, et al.
Published: (2021) -
Vsebnost ekstraktivov v skorji in lesu robinije (Robinia pseudoacacia L.)
by: Viljem Vek, et al.
Published: (2019)