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Improving Sound Event Classification by Increasing Shift Invariance in
  Convolutional Neural Networks

Improving Sound Event Classification by Increasing Shift Invariance in Convolutional Neural Networks

1 July 2021
Eduardo Fonseca
Andrés Ferraro
Xavier Serra
    AI4TS
ArXivPDFHTML

Papers citing "Improving Sound Event Classification by Increasing Shift Invariance in Convolutional Neural Networks"

4 / 4 papers shown
Title
BYOL for Audio: Exploring Pre-trained General-purpose Audio
  Representations
BYOL for Audio: Exploring Pre-trained General-purpose Audio Representations
Daisuke Niizumi
Daiki Takeuchi
Yasunori Ohishi
N. Harada
K. Kashino
SSL
36
53
0
15 Apr 2022
Learning strides in convolutional neural networks
Learning strides in convolutional neural networks
Rachid Riad
O. Teboul
David Grangier
Neil Zeghidour
36
41
0
03 Feb 2022
LEAF: A Learnable Frontend for Audio Classification
LEAF: A Learnable Frontend for Audio Classification
Neil Zeghidour
O. Teboul
Félix de Chaumont Quitry
Marco Tagliasacchi
VLM
AAML
85
144
0
21 Jan 2021
FSD50K: An Open Dataset of Human-Labeled Sound Events
FSD50K: An Open Dataset of Human-Labeled Sound Events
Eduardo Fonseca
Xavier Favory
Jordi Pons
F. Font
Xavier Serra
24
436
0
01 Oct 2020
1