Zobrazeno 1 - 10
of 460
pro vyhledávání: '"DIALLO, Boubacar"'
Publikováno v:
IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), IEEE/CVF, Jun 2024, Seattle, United States
The deployment of safe and trustworthy machine learning systems, and particularly complex black box neural networks, in real-world applications requires reliable and certified guarantees on their performance. The conformal prediction framework offers
Externí odkaz:
http://arxiv.org/abs/2406.08884
Autor:
van Marrewijk, Bart M., Dandjinou, Charbel, Rustia, Dan Jeric Arcega, Gonzalez, Nicolas Franco, Diallo, Boubacar, Dias, Jérôme, Melki, Paul, Blok, Pieter M.
Optimizing deep learning models requires large amounts of annotated images, a process that is both time-intensive and costly. Especially for semantic segmentation models in which every pixel must be annotated. A potential strategy to mitigate annotat
Externí odkaz:
http://arxiv.org/abs/2404.02580
Publikováno v:
2023 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW), IEEE/CVF, Oct 2023, Paris, France
As deep learning predictive models become an integral part of a large spectrum of precision agricultural systems, a barrier to the adoption of such automated solutions is the lack of user trust in these highly complex, opaque and uncertain models. In
Externí odkaz:
http://arxiv.org/abs/2308.15094
Publikováno v:
Computational and Mathematical Biophysics, Vol 12, Iss 1, Pp 26-40 (2024)
Infectious illnesses like hepatitis place a heavy cost on global health, and precise mathematical models must be created in order to understand and manage them. The Adomian decomposition method (ADM) and an optimal control strategy are utilized to so
Externí odkaz:
https://doaj.org/article/dd66aac21c7f41c388a67b7fc4cb324e