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Publication : Electrical Engineering and Systems Science > Image and Video Processing

JDLL: A library to run Deep Learning models on Java bioimage informatics platforms

Team: Biological Image Analysis
Team: Image Analysis Hub
Member: Thomas Musset
Member: Jean-Yves Tinevez
Member: Jean-Christophe Olivo-Marin
Scientific Fields
Diseases
Organisms
Applications
Technique

Published in Electrical Engineering and Systems Science > Image and Video Processing - 07 Jun 2023

Carlos Garcia Lopez de Haro, Stephane Dallongeville, Thomas Musset, Estibaliz Gomez de Mariscal, Daniel Sage, Wei Ouyang, Arrate Munoz-Barrutia, Jean-Yves Tinevez, Jean-Christophe Olivo-Marin

Link to DOI – 10.48550

We present JDLL, an agile Java library that offers a comprehensive toolset/API to unify the development of high-end applications of DL for bioimage analysis and to streamline their installation and maintenance. JDLL provides all the functions required to consume DL models seamlessly, without being burdened by the configuration of the Python-based DL frameworks, within Java bioimage informatics platforms. Moreover, it allows the deployment of pre-trained models in the Bioimage Model Zoo (BMZ) by shipping the logic to connect to the BMZ website, download and run a selected model inference.