Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Przemysław Jabłecki"'
Publikováno v:
Computational Science – ICCS 2022 ISBN: 9783031087530
Federated learning enables building a shared model from multicentre data while storing the training data locally for privacy. In this paper, we present an evaluation (called CXR-FL) of deep learning-based models for chest X-ray image analysis using t
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::efe1ebdfd6b22e5a23aa772c714885ff
https://zenodo.org/record/7013337
https://zenodo.org/record/7013337
Autor:
Jacek Dajda, Michał Idzik, Jakub Sroka, Mikołaj Sikora, Wiktor Pawłowski, Maciej Smołka, Przemysław Jabłecki, Filip Ślazyk, Maciej Malawski, Emilia Majerz, Aleksandra Pasternak, Witold Dzwinel, Wojciech Kania, Bogumiła Hnatkowska, Wojciech Thomas, Joanna Świebocka-Więk, Andrzej Paszkiewicz
Publikováno v:
Computing and Informatics
COMPUTING AND INFORMATICS; Vol. 40 No. 4 (2021): Computing and Informatics; 930–956
COMPUTING AND INFORMATICS; Vol. 40 No. 4 (2021): Computing and Informatics; 930–956
This article presents short analysis and observations on current trends and directions in conducting engineering theses in the field of computer science. This report is based on collected bachelor theses in AGH Computer Science Department for academi
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783030908737
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Clinical Image-Based Procedures, Distributed and Collaborative Learning, Artificial Intelligence for Combating COVID-19 and Secure and Privacy-Preserving Machine Learning
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5f6c75fa92b4c1bade498a9742e28b3c
https://doi.org/10.1007/978-3-030-90874-4_11
https://doi.org/10.1007/978-3-030-90874-4_11