Zobrazeno 1 - 10
of 25
pro vyhledávání: '"Tamaazousti, Youssef"'
Neural Transfer Learning (TL) is becoming ubiquitous in Natural Language Processing (NLP), thanks to its high performance on many tasks, especially in low-resourced scenarios. Notably, TL is widely used for neural domain adaptation to transfer valuab
Externí odkaz:
http://arxiv.org/abs/2106.04935
Autor:
Tamaazousti, Youssef
En raison de ses enjeux sociétaux, économiques et culturels, l’intelligence artificielle (dénotée IA) est aujourd’hui un sujet d’actualité très populaire. L’un de ses principaux objectifs est de développer des systèmes qui facilitent
Externí odkaz:
http://www.theses.fr/2018SACLC038/document
We tackle the problem of texture inpainting where the input images are textures with missing values along with masks that indicate the zones that should be generated. Many works have been done in image inpainting with the aim to achieve global and lo
Externí odkaz:
http://arxiv.org/abs/1911.02274
A food recipe is an ordered set of instructions for preparing a particular dish. From a visual perspective, every instruction step can be seen as a way to change the visual appearance of the dish by adding extra objects (e.g., adding an ingredient) o
Externí odkaz:
http://arxiv.org/abs/1906.02839
Fine-tuning neural networks is widely used to transfer valuable knowledge from high-resource to low-resource domains. In a standard fine-tuning scheme, source and target problems are trained using the same architecture. Although capable of adapting t
Externí odkaz:
http://arxiv.org/abs/1904.03595
Autor:
Lin, John, Seddik, Mohamed El Amine, Tamaazousti, Mohamed, Tamaazousti, Youssef, Bartoli, Adrien
We propose a novel learning approach, in the form of a fully-convolutional neural network (CNN), which automatically and consistently removes specular highlights from a single image by generating its diffuse component. To train the generative network
Externí odkaz:
http://arxiv.org/abs/1904.02672
Many real-world visual recognition use-cases can not directly benefit from state-of-the-art CNN-based approaches because of the lack of many annotated data. The usual approach to deal with this is to transfer a representation pre-learned on a large a
Externí odkaz:
http://arxiv.org/abs/1810.02126
Autor:
Tamaazousti, Youssef, Borgne, Hervé Le, Hudelot, Céline, Seddik, Mohamed El Amine, Tamaazousti, Mohamed
A representation is supposed universal if it encodes any element of the visual world (e.g., objects, scenes) in any configuration (e.g., scale, context). While not expecting pure universal representations, the goal in the literature is to improve the
Externí odkaz:
http://arxiv.org/abs/1712.09708
Autor:
Tamaazousti, Youssef, Le Borgne, Hervé, Popescu, Adrian, Gadeski, Etienne, Ginsca, Alexandru, Hudelot, Céline
Publikováno v:
In Computer Vision and Image Understanding October 2017 163:41-57
Autor:
Tamaazousti, Youssef1,2 youssef.tamaazousti@cea.fr, Le Borgne, Hervé1 herve.leborgne@cea.fr, Popescu, Adrian1 adrian.popescu@cea.fr, Gadeski, Étienne1 etienne.gadeski@cea.fr, Ginsca, Alexandru1 alexandru.ginsca@cea.fr, Hudelot, Céline2 celine.hudelot@centralesupelec.fr
Publikováno v:
Traitement du Signal. 2017 Special Issue, Vol. 34, p9-34. 26p.