Zobrazeno 1 - 10
of 7 480
pro vyhledávání: '"A, Gröger"'
Autor:
Liu, Puze, Günster, Jonas, Funk, Niklas, Gröger, Simon, Chen, Dong, Bou-Ammar, Haitham, Jankowski, Julius, Marić, Ante, Calinon, Sylvain, Orsula, Andrej, Olivares-Mendez, Miguel, Zhou, Hongyi, Lioutikov, Rudolf, Neumann, Gerhard, Zhalehmehrabi, Amarildo Likmeta Amirhossein, Bonenfant, Thomas, Restelli, Marcello, Tateo, Davide, Liu, Ziyuan, Peters, Jan
Machine learning methods have a groundbreaking impact in many application domains, but their application on real robotic platforms is still limited. Despite the many challenges associated with combining machine learning technology with robotics, robo
Externí odkaz:
http://arxiv.org/abs/2411.05718
Autor:
Gröger, Fabian, Gottfrois, Philippe, Amruthalingam, Ludovic, Gonzalez-Jimenez, Alvaro, Lionetti, Simone, Soenksen-Martinez, Luis R., Navarini, Alexander A., Pouly, Marc
The growing demand for accurate and equitable AI models in digital dermatology faces a significant challenge: the lack of diverse, high-quality labeled data. In this work, we investigate the potential of domain-specific foundation models for dermatol
Externí odkaz:
http://arxiv.org/abs/2411.05514
Autor:
Gottfrois, Philippe, Gröger, Fabian, Andriambololoniaina, Faly Herizo, Amruthalingam, Ludovic, Gonzalez-Jimenez, Alvaro, Hsu, Christophe, Kessy, Agnes, Lionetti, Simone, Mavura, Daudi, Ng'ambi, Wingston, Ngongonda, Dingase Faith, Pouly, Marc, Rakotoarisaona, Mendrika Fifaliana, Rabenja, Fahafahantsoa Rapelanoro, Traoré, Ibrahima, Navarini, Alexander A.
Publikováno v:
Medical Image Computing and Computer Assisted Intervention -- MICCAI 2024, MICCAI 2024, Lecture Notes in Computer Science, vol. 15003, Springer, Cham
Africa faces a huge shortage of dermatologists, with less than one per million people. This is in stark contrast to the high demand for dermatologic care, with 80% of the paediatric population suffering from largely untreated skin conditions. The int
Externí odkaz:
http://arxiv.org/abs/2411.04584
Root Cause Analysis (RCA) is a quality management method that aims to systematically investigate and identify the cause-and-effect relationships of problems and their underlying causes. Traditional methods are based on the analysis of problems by sub
Externí odkaz:
http://arxiv.org/abs/2407.16388
Real-time bioaerosol monitoring is improving the quality of life for people affected by allergies, but it often relies on deep-learning models which pose challenges for widespread adoption. These models are typically trained in a supervised fashion a
Externí odkaz:
http://arxiv.org/abs/2406.09984
Autor:
Gonzalez-Jimenez, Alvaro, Lionetti, Simone, Bazazian, Dena, Gottfrois, Philippe, Gröger, Fabian, Pouly, Marc, Navarini, Alexander
Out-Of-Distribution (OOD) detection is critical to deploy deep learning models in safety-critical applications. However, the inherent hierarchical concept structure of visual data, which is instrumental to OOD detection, is often poorly captured by c
Externí odkaz:
http://arxiv.org/abs/2403.15260
Autor:
Gröger, Fabian, Lionetti, Simone, Gottfrois, Philippe, Gonzalez-Jimenez, Alvaro, Groh, Matthew, Daneshjou, Roxana, Consortium, Labelling, Navarini, Alexander A., Pouly, Marc
Publikováno v:
Proceedings of the 3rd Machine Learning for Health Symposium, PMLR 225:101-128, 2023
Benchmark datasets for digital dermatology unwittingly contain inaccuracies that reduce trust in model performance estimates. We propose a resource-efficient data-cleaning protocol to identify issues that escaped previous curation. The protocol lever
Externí odkaz:
http://arxiv.org/abs/2309.06961
Publikováno v:
Gr\"oger, Fabian; Pouly, Marc; Tinner, Flavia & Brandes, Leif (2022). Assessing Guest Nationality Composition from Hotel Reviews. Proceedings of the 9th Swiss Data Science Conference, 1
Many hotels target guest acquisition efforts to specific markets in order to best anticipate individual preferences and needs of their guests. Likewise, such strategic positioning is a prerequisite for efficient marketing budget allocation. Official
Externí odkaz:
http://arxiv.org/abs/2308.06175
Publikováno v:
Communications Earth & Environment, Vol 5, Iss 1, Pp 1-3 (2024)
Externí odkaz:
https://doaj.org/article/5f58779f2f2845b8a9588a3bb770d874
Autor:
Gonzalez-Jimenez, Alvaro, Lionetti, Simone, Gottfrois, Philippe, Gröger, Fabian, Pouly, Marc, Navarini, Alexander
This paper presents a new robust loss function, the T-Loss, for medical image segmentation. The proposed loss is based on the negative log-likelihood of the Student-t distribution and can effectively handle outliers in the data by controlling its sen
Externí odkaz:
http://arxiv.org/abs/2306.00753