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pro vyhledávání: '"A. Hubens"'
Sketch-Based Image Retrieval (SBIR) is a crucial task in multimedia retrieval, where the goal is to retrieve a set of images that match a given sketch query. Researchers have already proposed several well-performing solutions for this task, but most
Externí odkaz:
http://arxiv.org/abs/2305.18988
Autor:
Hubens, Nathan, Delvigne, Victor, Mancas, Matei, Gosselin, Bernard, Preda, Marius, Zaharia, Titus
The advent of sparsity inducing techniques in neural networks has been of a great help in the last few years. Indeed, those methods allowed to find lighter and faster networks, able to perform more efficiently in resource-constrained environment such
Externí odkaz:
http://arxiv.org/abs/2303.10999
Autor:
Hubens, Nathan
FasterAI is a PyTorch-based library, aiming to facilitate the utilization of deep neural networks compression techniques such as sparsification, pruning, knowledge distillation, or regularization. The library is built with the purpose of enabling qui
Externí odkaz:
http://arxiv.org/abs/2207.01088
Neural network pruning is a widely used strategy for reducing model storage and computing requirements. It allows to lower the complexity of the network by introducing sparsity in the weights. Because taking advantage of sparse matrices is still chal
Externí odkaz:
http://arxiv.org/abs/2203.05807
In the past few years, neural character animation has emerged and offered an automatic method for animating virtual characters. Their motion is synthesized by a neural network. Controlling this movement in real time with a user-defined control signal
Externí odkaz:
http://arxiv.org/abs/2201.04042
Autor:
Delvigne, Victor, Tits, Noé, La Fisca, Luca, Hubens, Nathan, Maiorca, Antoine, Wannous, Hazem, Dutoit, Thierry, Vandeborre, Jean-Philippe
Visual attention estimation is an active field of research at the crossroads of different disciplines: computer vision, artificial intelligence and medicine. One of the most common approaches to estimate a saliency map representing attention is based
Externí odkaz:
http://arxiv.org/abs/2201.03902
An Experimental Study of the Impact of Pre-training on the Pruning of a Convolutional Neural Network
In recent years, deep neural networks have known a wide success in various application domains. However, they require important computational and memory resources, which severely hinders their deployment, notably on mobile devices or for real-time ap
Externí odkaz:
http://arxiv.org/abs/2112.08227
Autor:
Azhaar Ahmad Ashraf, Manal Aljuhani, Chantal J. Hubens, Jérôme Jeandriens, Harold G. Parkes, Kalotina Geraki, Ayesha Mahmood, Amy H. Herlihy, Po-Wah So
Publikováno v:
Frontiers in Aging Neuroscience, Vol 16 (2024)
Iron dyshomeostasis and neuroinflammation, characteristic features of the aged brain, and exacerbated in neurodegenerative disease, may induce oxidative stress-mediated neurodegeneration. In this study, the effects of potential priming with mild syst
Externí odkaz:
https://doaj.org/article/32631ab5e47c408aa0a899ac30d736af
Introducing sparsity in a neural network has been an efficient way to reduce its complexity while keeping its performance almost intact. Most of the time, sparsity is introduced using a three-stage pipeline: 1) train the model to convergence, 2) prun
Externí odkaz:
http://arxiv.org/abs/2107.02086
Autor:
Niel Merckx, Laurence Claes, Maud De Venter, Philip Plaeke, Anthony Beunis, Martin Ruppert, Guy Hubens, Filip Van Den Eede
Publikováno v:
Eating and Weight Disorders, Vol 29, Iss 1, Pp 1-3 (2024)
Externí odkaz:
https://doaj.org/article/6728f151e85f4ebe8298b92e676c37da