Zobrazeno 1 - 10
of 316
pro vyhledávání: '"Bugeau, A."'
Digitalization appears as a lever to enhance agriculture sustainability. However, existing works on digital agriculture's own sustainability remain scarce, disregarding the environmental effects of deploying digital devices on a large-scale. We propo
Externí odkaz:
http://arxiv.org/abs/2409.17617
Autor:
Bugeau, Aurélie, Ligozat, Anne-Laure
With the climate change context, many prospective studies, generally encompassing all areas of society, imagine possible futures to expand the range of options. The role of digital technologies within these possible futures is rarely specifically tar
Externí odkaz:
http://arxiv.org/abs/2312.15948
Machine learning and deep learning models have become essential in the recent fast development of artificial intelligence in many sectors of the society. It is now widely acknowledge that the development of these models has an environmental cost that
Externí odkaz:
http://arxiv.org/abs/2306.08323
Publikováno v:
International Conference on Information and Communications Technology for Sustainability (ICT4S), 2023, Rennes, France
Assessing the energy consumption or carbon footprint of data distribution of video streaming services is usually carried out through energy or carbon intensity figures (in Wh or gCO2e per GB). In this paper, we first review the reasons why such appro
Externí odkaz:
http://arxiv.org/abs/2304.03151
In this paper, we propose a patch-based architecture for multi-label classification problems where only a single positive label is observed in images of the dataset. Our contributions are twofold. First, we introduce a light patch architecture based
Externí odkaz:
http://arxiv.org/abs/2209.06530
Image inpainting refers to the restoration of an image with missing regions in a way that is not detectable by the observer. The inpainting regions can be of any size and shape. This is an ill-posed inverse problem that does not have a unique solutio
Externí odkaz:
http://arxiv.org/abs/2205.02146
Autor:
Ballester, Coloma, Bugeau, Aurélie, Carrillo, Hernan, Clément, Michaël, Giraud, Rémi, Raad, Lara, Vitoria, Patricia
Image colorization aims to add color information to a grayscale image in a realistic way. Recent methods mostly rely on deep learning strategies. While learning to automatically colorize an image, one can define well-suited objective functions relate
Externí odkaz:
http://arxiv.org/abs/2204.02980
Autor:
Ballester, Coloma, Bugeau, Aurélie, Carrillo, Hernan, Clément, Michaël, Giraud, Rémi, Raad, Lara, Vitoria, Patricia
Colorization is a process that converts a grayscale image into a color one that looks as natural as possible. Over the years this task has received a lot of attention. Existing colorization methods rely on different color spaces: RGB, YUV, Lab, etc.
Externí odkaz:
http://arxiv.org/abs/2204.02850
In the past ten years, artificial intelligence has encountered such dramatic progress that it is now seen as a tool of choice to solve environmental issues and in the first place greenhouse gas emissions (GHG). At the same time the deep learning comm
Externí odkaz:
http://arxiv.org/abs/2110.11822
We present an approach for detecting and estimating the 3D poses of objects in images that requires only an untextured CAD model and no training phase for new objects. Our approach combines Deep Learning and 3D geometry: It relies on an embedding of
Externí odkaz:
http://arxiv.org/abs/2010.04075