3 papers
cs.CV2024
Dilated Convolution with Learnable Spacings makes visual models more aligned with humans: a Grad-CAM study
Rabih Chamas, Ismail Khalfaoui-Hassani, Timothee Masquelier
Dilated Convolution with Learnable Spacing (DCLS) is a recent advanced convolution method that allows enlarging the receptive fields (RF) without increasing the number of parameter…
cs.SD2023
Audio classification with Dilated Convolution with Learnable Spacings
Ismail Khalfaoui-Hassani, Timothée Masquelier, Thomas Pellegrini
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.…
cs.SD2023
Adapting a ConvNeXt model to audio classification on AudioSet
Thomas Pellegrini, Ismail Khalfaoui-Hassani, Etienne Labbé +1
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…