Zobrazeno 1 - 10
of 228
pro vyhledávání: '"de Mathelin P"'
Autor:
Arbor, Nicolas, Bartolucci, Laurent, Dai, Botao, Azhar, Halima El, Galmiche, Pierre, Jarnet, Delphine, de Papigny, Michel de Mathelin, Meyer, Philippe, Seo, Hyewon
Publikováno v:
The 20th international conference on the use of computers in radiation therapy (ICCR), Jul 2024, Lyon, France. pp.834-836
Skin dose in radiotherapy is a key issue for reducing patient side effects, but dose calculations in this high-gradient region remains a challenge. To support radiation therapists and medical physicist in their decisions, a computational tool has bee
Externí odkaz:
http://arxiv.org/abs/2410.21823
Autor:
Lalou, Yanis, Gnassounou, Théo, Collas, Antoine, de Mathelin, Antoine, Kachaiev, Oleksii, Odonnat, Ambroise, Gramfort, Alexandre, Moreau, Thomas, Flamary, Rémi
Unsupervised Domain Adaptation (DA) consists of adapting a model trained on a labeled source domain to perform well on an unlabeled target domain with some data distribution shift. While many methods have been proposed in the literature, fair and rea
Externí odkaz:
http://arxiv.org/abs/2407.11676
This paper deals with uncertainty quantification and out-of-distribution detection in deep learning using Bayesian and ensemble methods. It proposes a practical solution to the lack of prediction diversity observed recently for standard approaches wh
Externí odkaz:
http://arxiv.org/abs/2309.15704
We consider the problem of uncertainty quantification in high dimensional regression and classification for which deep ensemble have proven to be promising methods. Recent observations have shown that deep ensemble often return overconfident estimate
Externí odkaz:
http://arxiv.org/abs/2304.04042
Autor:
Liu, Rongrong, Wandeto, John M., Nageotte, Florent, Zanne, Philippe, de Mathelin, Michel, Dresp-Langley, Birgitta
Publikováno v:
Bioengineering, 2023; 10(1):59
This paper builds on our previous work by exploiting Artificial Intelligence to predict individual grip force variability in manual robot control. Grip forces were recorded from various loci in the dominant and non dominant hands of individuals by me
Externí odkaz:
http://arxiv.org/abs/2303.01995
Publikováno v:
Astronomy, Vol 3, Iss 3, Pp 189-207 (2024)
In astronomy, understanding the evolutionary trajectories of galaxies necessitates a robust analysis of their star formation histories (SFHs), a task complicated by our inability to observe these vast celestial entities throughout their billion-year
Externí odkaz:
https://doaj.org/article/bc0b7d492bcf4ab09706d4e5a98521ab
Autor:
Lazo, Jorge F., Rosa, Benoit, Catellani, Michele, Fontana, Matteo, Mistretta, Francesco A., Musi, Gennaro, de Cobelli, Ottavio, de Mathelin, Michel, De Momi, Elena
Objective: Accurate visual classification of bladder tissue during Trans-Urethral Resection of Bladder Tumor (TURBT) procedures is essential to improve early cancer diagnosis and treatment. During TURBT interventions, White Light Imaging (WLI) and Na
Externí odkaz:
http://arxiv.org/abs/2212.11375
Bias in datasets can be very detrimental for appropriate statistical estimation. In response to this problem, importance weighting methods have been developed to match any biased distribution to its corresponding target unbiased distribution. The sem
Externí odkaz:
http://arxiv.org/abs/2209.04215
Autor:
Lazo, Jorge F., Lai, Chun-Feng, Moccia, Sara, Rosa, Benoit, Catellani, Michele, de Mathelin, Michel, Ferrigno, Giancarlo, Breedveld, Paul, Dankelman, Jenny, De Momi, Elena
Navigation inside luminal organs is an arduous task that requires non-intuitive coordination between the movement of the operator's hand and the information obtained from the endoscopic video. The development of tools to automate certain tasks could
Externí odkaz:
http://arxiv.org/abs/2207.00401
Publikováno v:
Astronomy 2024, 3(3), 189-207
The prevalent paradigm of machine learning today is to use past observations to predict future ones. What if, however, we are interested in knowing the past given the present? This situation is indeed one that astronomers must contend with often. To
Externí odkaz:
http://arxiv.org/abs/2112.14072