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Addressing Missing Labels in Large-Scale Sound Event Recognition Using a
  Teacher-Student Framework With Loss Masking

Addressing Missing Labels in Large-Scale Sound Event Recognition Using a Teacher-Student Framework With Loss Masking

2 May 2020
Eduardo Fonseca
Shawn Hershey
Manoj Plakal
D. Ellis
A. Jansen
R. C. Moore
Xavier Serra
    NoLa
ArXivPDFHTML

Papers citing "Addressing Missing Labels in Large-Scale Sound Event Recognition Using a Teacher-Student Framework With Loss Masking"

15 / 15 papers shown
Title
PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern
  Recognition
PANNs: Large-Scale Pretrained Audio Neural Networks for Audio Pattern Recognition
Qiuqiang Kong
Yin Cao
Turab Iqbal
Yuxuan Wang
Wenwu Wang
Mark D. Plumbley
VLM
SSL
174
1,074
0
21 Dec 2019
Confident Learning: Estimating Uncertainty in Dataset Labels
Confident Learning: Estimating Uncertainty in Dataset Labels
Curtis G. Northcutt
Lu Jiang
Isaac L. Chuang
NoLa
113
687
0
31 Oct 2019
Model-agnostic Approaches to Handling Noisy Labels When Training Sound
  Event Classifiers
Model-agnostic Approaches to Handling Noisy Labels When Training Sound Event Classifiers
Eduardo Fonseca
F. Font
Xavier Serra
NoLa
56
9
0
26 Oct 2019
Audio tagging with noisy labels and minimal supervision
Audio tagging with noisy labels and minimal supervision
Eduardo Fonseca
Manoj Plakal
F. Font
D. Ellis
Xavier Serra
44
93
0
07 Jun 2019
Learning Sound Event Classifiers from Web Audio with Noisy Labels
Learning Sound Event Classifiers from Web Audio with Noisy Labels
Eduardo Fonseca
Manoj Plakal
D. Ellis
F. Font
Xavier Favory
Xavier Serra
NoLa
60
110
0
04 Jan 2019
Learning Sound Events From Webly Labeled Data
Learning Sound Events From Webly Labeled Data
Anurag Kumar
Ankit Parag Shah
Bhiksha Raj
Alexander G. Hauptmann
NoLa
46
12
0
25 Nov 2018
General-purpose Tagging of Freesound Audio with AudioSet Labels: Task
  Description, Dataset, and Baseline
General-purpose Tagging of Freesound Audio with AudioSet Labels: Task Description, Dataset, and Baseline
Eduardo Fonseca
Manoj Plakal
F. Font
D. Ellis
Xavier Favory
Jordi Pons
Xavier Serra
83
148
0
26 Jul 2018
A Closer Look at Weak Label Learning for Audio Events
A Closer Look at Weak Label Learning for Audio Events
Ankit Parag Shah
Anurag Kumar
Alexander G. Hauptmann
Bhiksha Raj
55
65
0
24 Apr 2018
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
Revisiting Unreasonable Effectiveness of Data in Deep Learning Era
Chen Sun
Abhinav Shrivastava
Saurabh Singh
Abhinav Gupta
VLM
172
2,393
0
10 Jul 2017
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision
  Applications
MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications
Andrew G. Howard
Menglong Zhu
Bo Chen
Dmitry Kalenichenko
Weijun Wang
Tobias Weyand
M. Andreetto
Hartwig Adam
3DH
1.1K
20,813
0
17 Apr 2017
CNN Architectures for Large-Scale Audio Classification
CNN Architectures for Large-Scale Audio Classification
Shawn Hershey
Sourish Chaudhuri
D. Ellis
J. Gemmeke
A. Jansen
...
Rif A. Saurous
Bryan Seybold
M. Slaney
Ron J. Weiss
K. Wilson
111
2,494
0
29 Sep 2016
Deep Residual Learning for Image Recognition
Deep Residual Learning for Image Recognition
Kaiming He
Xinming Zhang
Shaoqing Ren
Jian Sun
MedIm
2.0K
193,426
0
10 Dec 2015
Distilling the Knowledge in a Neural Network
Distilling the Knowledge in a Neural Network
Geoffrey E. Hinton
Oriol Vinyals
J. Dean
FedML
318
19,609
0
09 Mar 2015
Adam: A Method for Stochastic Optimization
Adam: A Method for Stochastic Optimization
Diederik P. Kingma
Jimmy Ba
ODL
1.5K
149,842
0
22 Dec 2014
Do Deep Nets Really Need to be Deep?
Do Deep Nets Really Need to be Deep?
Lei Jimmy Ba
R. Caruana
160
2,117
0
21 Dec 2013
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