Treffer: JDLL: a library to run deep learning models on Java bioimage informatics platforms

Title:
JDLL: a library to run deep learning models on Java bioimage informatics platforms
Contributors:
Analyse d'images biologiques - Biological Image Analysis (BIA), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Instituto Gulbenkian de Ciência [Oeiras] (IGC), Fundação Calouste Gulbenkian = Fondation Calouste Gulbenkian = Calouste Gulbenkian Foundation [Lisbonne], Ecole Polytechnique Fédérale de Lausanne (EPFL), KTH Royal Institute of Technology [Stockholm] (KTH), Universidad Carlos III de Madrid [Madrid] (UC3M), work has been partially supported by the Agence Nationale de la Recherche through the LabEx IBEID (ANR-10-LABX-62-IBEID), the Institut Carnot Pasteur Microbes & Santé (ANR 16 CARN 0023-01), the programs PIA INCEPTION (ANR-16-CONV-0005) and France-BioImaging (ANR-10-INBS-04), by DIM ELICIT Région Ile-de-France, by the European Commission through the H2020-FET-OPEN-2018–2019-2020-01 grant no. 862840 (“FREE@POC”) (J.-C.O.-M.), by additional internal funding from the Bioimage Analysis unit and the Institut Pasteur (J.-C.O.-M. and J.-Y.T.), by the Ministerio de Ciencia, Innovación y Universidades, Agencia Estatal de Investigación, under grant PID2019-109820RB-I00, MCIN / AEI / 10.13039/501100011033/, co-financed by European Regional Development Fund (ERDF), “A way of making Europe,” and the European Commission through the Horizon Europe program (AI4LIFE project, grant agreement 101057970-AI4LIFE) (A.M.-B.), and by Fundação Calouste Gulbenkian and EMBO Postdoctoral Fellowship (EMBO ALTF 174-2022) (E.G.M.)., ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), ANR-10-LABX-0062,IBEID,Integrative Biology of Emerging Infectious Diseases(2010), ANR-10-INBS-0004,France-BioImaging,Développment d'une infrastructure française distribuée coordonnée(2010), European Project: 862840,H2020-FETOPEN-2018-2019-2020-01,FreeATPOC(2020), European Project: 101057970,HORIZON-INFRA-2021-SERV-01,AI4LIFE(2022)
Source:
Nature Methods. 21(1):7-8
Publisher Information:
CCSD; Nature Publishing Group, 2024.
Publication Year:
2024
Collection:
collection:PASTEUR
collection:CNRS
collection:UNIV-PARIS
collection:UNIVERSITE-PARIS
collection:ANR
collection:BIOLOGICAL-IMAGE-ANALYSIS
collection:UMR3691
Original Identifier:
PUBMED: 38191929
HAL: hal-04580174
Document Type:
Zeitschrift article<br />Journal articles
Language:
English
ISSN:
1548-7091
1548-7105
Relation:
info:eu-repo/semantics/altIdentifier/doi/10.1038/s41592-023-02129-x; info:eu-repo/semantics/altIdentifier/pmid/38191929; info:eu-repo/grantAgreement//862840/EU/Towards an instrument-free future of molecular diagnostics at the point-of-care/FreeATPOC; info:eu-repo/grantAgreement//101057970/EU/Artificial Intelligence for Image Data Analysis in the Life Sciences/AI4LIFE
DOI:
10.1038/s41592-023-02129-x
Rights:
info:eu-repo/semantics/OpenAccess
URL: http://creativecommons.org/licenses/by-nc/
Accession Number:
edshal.hal.04580174v1
Database:
HAL