Zobrazeno 1 - 10
of 80
pro vyhledávání: '"Khodabandelou, Ghazaleh"'
The integration of Artificial Intelligence (AI) and the Internet of Medical Things (IoMT) in healthcare, through Machine Learning (ML) and Deep Learning (DL) techniques, has advanced the prediction and diagnosis of chronic diseases. AI-driven models
Externí odkaz:
http://arxiv.org/abs/2410.00034
Publikováno v:
2023 IEEE 36th International Symposium on Computer-Based Medical Systems (2023) 700-705
Post-traumatic stress disorder (PTSD) is a mental disorder that can be developed after witnessing or experiencing extremely traumatic events. PTSD can affect anyone, regardless of ethnicity, or culture. An estimated one in every eleven people will ex
Externí odkaz:
http://arxiv.org/abs/2403.19441
Publikováno v:
In Computer Methods and Programs in Biomedicine December 2024 257
Publikováno v:
In Biomedical Signal Processing and Control March 2024 89
The performance of Human Activity Recognition (HAR) models, particularly deep neural networks, is highly contingent upon the availability of the massive amount of annotated training data which should be sufficiently labeled. Though, data acquisition
Externí odkaz:
http://arxiv.org/abs/2012.03682
Autor:
Chiaroni, Florent, Khodabandelou, Ghazaleh, Rahal, Mohamed-Cherif, Hueber, Nicolas, Dufaux, Frederic
With surge of available but unlabeled data, Positive Unlabeled (PU) learning is becoming a thriving challenge. This work deals with this demanding task for which recent GAN-based PU approaches have demonstrated promising results. Generative adversari
Externí odkaz:
http://arxiv.org/abs/1910.01968
Publikováno v:
In Engineering Applications of Artificial Intelligence February 2023 118
Publikováno v:
In Knowledge-Based Systems 25 January 2023 260
Publikováno v:
IEEE Transaction on Mobile Computing, 2018
Communication-enabled devices routinely carried by individuals have become pervasive, opening unprecedented opportunities for collecting digital metadata about the mobility of large populations. In this paper, we propose a novel methodology for the e
Externí odkaz:
http://arxiv.org/abs/1810.12909
Publikováno v:
In Neurocomputing 21 August 2022 500:649-661