Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Bertrand, Hadrien"'
Autor:
Cohen, Joseph Paul, Viviano, Joseph D., Bertin, Paul, Morrison, Paul, Torabian, Parsa, Guarrera, Matteo, Lungren, Matthew P, Chaudhari, Akshay, Brooks, Rupert, Hashir, Mohammad, Bertrand, Hadrien
TorchXRayVision is an open source software library for working with chest X-ray datasets and deep learning models. It provides a common interface and common pre-processing chain for a wide set of publicly available chest X-ray datasets. In addition,
Externí odkaz:
http://arxiv.org/abs/2111.00595
Autor:
Bertrand, Hadrien
Ces dernières années, l'apprentissage profond a complètement changé le domaine de vision par ordinateur. Plus rapide, donnant de meilleurs résultats, et nécessitant une expertise moindre pour être utilisé que les méthodes classiques de visio
Externí odkaz:
http://www.theses.fr/2019SACLT001/document
Most deep learning models in chest X-ray prediction utilize the posteroanterior (PA) view due to the lack of other views available. PadChest is a large-scale chest X-ray dataset that has almost 200 labels and multiple views available. In this work, w
Externí odkaz:
http://arxiv.org/abs/2002.02582
This large scale study focuses on quantifying what X-rays diagnostic prediction tasks generalize well across multiple different datasets. We present evidence that the issue of generalization is not due to a shift in the images but instead a shift in
Externí odkaz:
http://arxiv.org/abs/2002.02497
Most convolutional neural networks in chest radiology use only the frontal posteroanterior (PA) view to make a prediction. However the lateral view is known to help the diagnosis of certain diseases and conditions. The recently released PadChest data
Externí odkaz:
http://arxiv.org/abs/1904.08534
The classification of MRI images according to the anatomical field of view is a necessary task to solve when faced with the increasing quantity of medical images. In parallel, advances in deep learning makes it a suitable tool for computer vision pro
Externí odkaz:
http://arxiv.org/abs/1701.04355
Autor:
Bertrand, Hadrien
Publikováno v:
Machine Learning [cs.LG]. Université Paris-Saclay, 2019. English. ⟨NNT : 2019SACLT001⟩
In the last few years, deep learning has changed irrevocably the field of computer vision. Faster, giving better results, and requiring a lower degree of expertise to use than traditional computer vision methods, deep learning has become ubiquitous i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ea5b3ea285475c43c81a0431d6690aea
https://pastel.archives-ouvertes.fr/tel-02089414
https://pastel.archives-ouvertes.fr/tel-02089414
Publikováno v:
CAp
CAp, 2017, Grenoble, France
CAp, 2017, Grenoble, France
National audience; One common problem in building deep learning architectures is the choice of the hyper-parameters. Among the various existing strategies, we propose to combine two complementary ones. On the one hand, the Hyperband method formalizes
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ef3b5347fbc598e493269328e167388e
https://hal.telecom-paris.fr/hal-02412262
https://hal.telecom-paris.fr/hal-02412262