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An Open-set Recognition and Few-Shot Learning Dataset for Audio Event
  Classification in Domestic Environments
v1v2v3v4v5v6v7v8 (latest)

An Open-set Recognition and Few-Shot Learning Dataset for Audio Event Classification in Domestic Environments

Pattern Recognition Letters (Pattern Recognit. Lett.), 2020
26 February 2020
Javier Naranjo-Alcazar
Sergi Perez-Castanos
P. Zuccarello
Ana M. Torres
Jose J. Lopez
Franscesc J. Ferri
M. Cobos
ArXiv (abs)PDFHTML

Papers citing "An Open-set Recognition and Few-Shot Learning Dataset for Audio Event Classification in Domestic Environments"

4 / 4 papers shown
Why do Angular Margin Losses work well for Semi-Supervised Anomalous
  Sound Detection?
Why do Angular Margin Losses work well for Semi-Supervised Anomalous Sound Detection?IEEE/ACM Transactions on Audio Speech and Language Processing (TASLP), 2023
Kevin Wilkinghoff
Frank Kurth
AAMLUQCV
231
22
0
27 Sep 2023
Learning to detect an animal sound from five examples
Learning to detect an animal sound from five examplesEcological Informatics (Ecol. Inform.), 2023
I. Nolasco
Shubhr Singh
V. Morfi
Vincent Lostanlen
A. Strandburg-Peshkin
...
Michael G. Emmerson
E. Versace
E. Grout
Haohe Liu
D. Stowell
309
57
0
22 May 2023
Dead Pixel Test Using Effective Receptive Field
Dead Pixel Test Using Effective Receptive FieldPattern Recognition Letters (PR), 2021
Bum Jun Kim
Hyeyeon Choi
Hyeonah Jang
Dong Gu Lee
Wonseok Jeong
Sang Woo Kim
165
33
0
31 Aug 2021
A Survey on Machine Learning from Few Samples
A Survey on Machine Learning from Few SamplesPattern Recognition (Pattern Recognit.), 2020
Jiang Lu
Pinghua Gong
Jieping Ye
Jianwei Zhang
Changshu Zhang
392
81
0
06 Sep 2020
1
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