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1812.04079
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DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal
7 December 2018
Stanislas Chambon
Valentin Thorey
P. Arnal
Emmanuel Mignot
Alexandre Gramfort
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Papers citing
"DOSED: a deep learning approach to detect multiple sleep micro-events in EEG signal"
12 / 12 papers shown
Title
From Sleep Staging to Spindle Detection: Evaluating End-to-End Automated Sleep Analysis
Niklas Grieger
S. Mehrkanoon
P. Ritter
Stephan Bialonski
29
0
0
08 May 2025
Unveil Sleep Spindles with Concentration of Frequency and Time
Riki Shimizu
Hau-tieng Wu
11
0
0
27 Oct 2023
Avoiding Post-Processing with Event-Based Detection in Biomedical Signals
N. Seeuws
Marina De Vos
Alexander Bertrand
11
2
0
22 Sep 2022
Advanced sleep spindle identification with neural networks
L. Kaulen
J. Schwabedal
Jules Schneider
P. Ritter
Stephan Bialonski
9
24
0
06 Feb 2022
Self-supervised Contrastive Learning for EEG-based Sleep Staging
Xue Jiang
Jianhui Zhao
Bo Du
Zhiyong Yuan
8
61
0
16 Sep 2021
MSED: a multi-modal sleep event detection model for clinical sleep analysis
Alexander Neergaard Zahid
P. Jennum
Emmanuel Mignot
H. Sørensen
35
10
0
07 Jan 2021
Deep Learning in EEG: Advance of the Last Ten-Year Critical Period
Shu Gong
Kaibo Xing
A. Cichocki
Junhua Li
VLM
32
64
0
22 Nov 2020
Automatic sleep stage classification with deep residual networks in a mixed-cohort setting
A. N. Olesen
P. Jennum
Emmanuel Mignot
H. Sørensen
23
65
0
21 Aug 2020
RED: Deep Recurrent Neural Networks for Sleep EEG Event Detection
Nicolás I. Tapia
P. Estévez
14
13
0
15 May 2020
Deep transfer learning for improving single-EEG arousal detection
A. N. Olesen
P. Jennum
Emmanuel Mignot
H. Sørensen
13
12
0
10 Apr 2020
AI vs Humans for the diagnosis of sleep apnea
Valentin Thorey
A. B. Hernández
P. Arnal
E. During
20
21
0
20 Jun 2019
Towards a Flexible Deep Learning Method for Automatic Detection of Clinically Relevant Multi-Modal Events in the Polysomnogram
A. N. Olesen
Stanislas Chambon
Valentin Thorey
P. Jennum
Emmanuel Mignot
H. Sørensen
26
7
0
16 May 2019
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