Zobrazeno 1 - 10
of 6 429
pro vyhledávání: '"Khalfaoui, A."'
Autor:
Mignon, Laurent1 (AUTHOR) laurent.mignon@orinst.ox.ac.uk
Publikováno v:
Journal of Islamic Studies. May2023, Vol. 34 Issue 2, p296-300. 5p.
Autor:
Khalfaoui-Hassani, Ismail
This thesis presents and evaluates the Dilated Convolution with Learnable Spacings (DCLS) method. Through various supervised learning experiments in the fields of computer vision, audio, and speech processing, the DCLS method proves to outperform bot
Externí odkaz:
http://arxiv.org/abs/2408.06383
Dilated Convolution with Learnable Spacing (DCLS) is a recent advanced convolution method that allows enlarging the receptive fields (RF) without increasing the number of parameters, like the dilated convolution, yet without imposing a regular grid.
Externí odkaz:
http://arxiv.org/abs/2408.03164
Publikováno v:
International Journal of Emerging Markets, 2023, Vol. 19, Issue 11, pp. 3709-3728.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJOEM-08-2022-1274
Publikováno v:
International Journal of Emerging Markets, 2023, Vol. 19, Issue 11, pp. 3938-3976.
Externí odkaz:
http://www.emeraldinsight.com/doi/10.1108/IJOEM-03-2022-0362
Autor:
Laurent Mignon
Publikováno v:
Journal of Islamic Studies. 34:296-300
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::22890659236f74b959534fa7478a20ce
https://doi.org/10.1093/jis/etac036
https://doi.org/10.1093/jis/etac036
Dilated convolution with learnable spacings (DCLS) is a recent convolution method in which the positions of the kernel elements are learned throughout training by backpropagation. Its interest has recently been demonstrated in computer vision (ImageN
Externí odkaz:
http://arxiv.org/abs/2309.13972
Autor:
Rommel, Cédric, Valle, Eduardo, Chen, Mickaël, Khalfaoui, Souhaiel, Marlet, Renaud, Cord, Matthieu, Pérez, Patrick
We present an innovative approach to 3D Human Pose Estimation (3D-HPE) by integrating cutting-edge diffusion models, which have revolutionized diverse fields, but are relatively unexplored in 3D-HPE. We show that diffusion models enhance the accuracy
Externí odkaz:
http://arxiv.org/abs/2309.01575
Publikováno v:
ICLR 2024
Spiking Neural Networks (SNNs) are a promising research direction for building power-efficient information processing systems, especially for temporal tasks such as speech recognition. In SNNs, delays refer to the time needed for one spike to travel
Externí odkaz:
http://arxiv.org/abs/2306.17670
In computer vision, convolutional neural networks (CNN) such as ConvNeXt, have been able to surpass state-of-the-art transformers, partly thanks to depthwise separable convolutions (DSC). DSC, as an approximation of the regular convolution, has made
Externí odkaz:
http://arxiv.org/abs/2306.00830