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Articles by Baptiste Magnier
Predicting Response to [177Lu]Lu-PSMA Therapy in mCRPC Using Machine Learning
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Preprocessing of Iris Images for BSIF-Based Biometric Systems: Binary Detected Edges and Iris Unwrapping
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited. For more information, please refer to https://www.mdpi.com/openaccess.
Preprocessing of Iris Images for BSIF-Based Biometric Systems: Binary Detected Edges and Iris Unwrapping
Preprint Article Version 1 This version is not peer-reviewed Version 1 : Received: 17 June 2024 / Approved: 18 June 2024 / Online: 18 June 2024 (11:20:53 CEST) Rubio, A.; Magnier, B. Preprocessing of Iris Images for BSIF-Based Biometric Systems: Binary Detected Edges and Iris Unwrapping. Preprints 2024, 2024061218. https://doi.org/10.20944/preprints202406.1218.v1 Rubio, A.; Magnier, B. Preprocessing of Iris Images for BSIF-Based Biometric Systems: Binary Detected Edges and Iris Unwrapping.
Revisiting Mehrotra and Nichani’s Corner Detection Method for Improvement with Truncated Anisotropic Gaussian Filtering
This is an early access version, the complete PDF, HTML, and XML versions will be available soon. Open AccessArticle by 1,*,† and 2,† 1 Euromov Digital Health in Motion, Univ Montpellier, IMT Mines Ales, Ales, France 2 College of Arts and Sciences, University of Nizwa, Nizwa 616, Oman * Author to whom correspondence should be addressed. † These authors contributed equally to this work.
L’apiculture dirigée par les données et les modèles
Les abeilles participent de façon notable à la biodiversité. La pollinisation est en effet une étape indispensable du cycle de vie des plantes, et les abeilles y contribuent pleinement. Cependant, les menaces qui pèsent aujourd’hui sur la biodiversité annoncent la disparition des insectes pollinisateurs, et en particulier celle des abeilles domestiques (comme l’Apis mellifera résidant en Europe).
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