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Mff-Rmpad: Multi-Scale Feature Fusion and Residual Mixed Parallel Attention Detector for Multiple Micro-Sleep Events Detection

https://doi.org/10.2139/ssrn.4872542
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CBAM: Convolutional Block Attention Module
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SSD: Single Shot MultiBox Detector
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Reduced Sleep Spindles and Spindle Coherence in Schizophrenia: Mechanisms of Impaired Memory Consolidation?
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Reduced Sleep Spindles in Schizophrenia: A Treatable Endophenotype That Links Risk Genes to Impaired Cognition?
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Signal processing techniques applied to human sleep EEG signals—A review
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An energy screening and morphology characterization-based hybrid expert scheme for automatic identification of micro-sleep event K-complex
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Multichannel sleep spindle detection using sparse low-rank optimization
inferredcites →https://doi.org/10.1016/j.jneumeth.2017.12.023openalex-extracted
A single channel sleep-spindle detector based on multivariate classification of EEG epochs: MUSSDET
inferredcites →https://doi.org/10.1016/j.jneumeth.2019.03.017openalex-extracted
DOSED: A deep learning approach to detect multiple sleep micro-events in EEG signal
inferredcites →https://doi.org/10.1038/nmeth.2855openalex-extracted
Sleep-spindle detection: crowdsourcing and evaluating performance of experts, non-experts and automated methods
inferredcites →https://doi.org/10.1109/10.184707openalex-extracted
Feature-based detection of the K-complex wave in the human electroencephalogram using neural networks
inferredcites →https://doi.org/10.1109/biocas.2015.7348373openalex-extracted
Application of random forest classifier for automatic sleep spindle detection
inferredcites →https://doi.org/10.1109/cvpr.2016.91openalex-extracted
You Only Look Once: Unified, Real-Time Object Detection
inferredcites →https://doi.org/10.1109/cvpr.2017.106openalex-extracted
Feature Pyramid Networks for Object Detection
inferredcites →https://doi.org/10.1109/iccv.2017.324openalex-extracted
Focal Loss for Dense Object Detection
inferredcites →https://doi.org/10.1109/ijcnn48605.2020.9207719openalex-extracted
RED: Deep Recurrent Neural Networks for Sleep EEG Event Detection
inferredcites →https://doi.org/10.1109/tbme.1970.4502759openalex-extracted
Automatic Detection of the K-Complex in Sleep Electroencephalograms
inferredcites →https://doi.org/10.1109/tnsre.2021.3105443openalex-extracted
SpindleU-Net: An Adaptive U-Net Framework for Sleep Spindle Detection in Single-Channel EEG
inferredcites →https://doi.org/10.1109/tpami.2016.2577031openalex-extracted
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
inferredcites →https://doi.org/10.1109/tpami.2018.2858826openalex-extracted
Focal Loss for Dense Object Detection
inferredcites →https://doi.org/10.1111/apha.12134openalex-extracted
Sleep, its regulation and possible mechanisms of sleep disturbances
inferredcites →https://doi.org/10.1111/jsr.12169openalex-extracted
Montreal Archive of Sleep Studies: an open‐access resource for instrument benchmarking and exploratory research
inferredcites →https://doi.org/10.1162/neco.1997.9.8.1735openalex-extracted
Long Short-Term Memory
inferredcites →https://doi.org/10.3389/fnhum.2015.00507openalex-extracted
Expert and crowd-sourced validation of an individualized sleep spindle detection method employing complex demodulation and individualized normalization
inferredcites →https://doi.org/10.3389/fninf.2017.00015openalex-extracted
Meet Spinky: An Open-Source Spindle and K-Complex Detection Toolbox Validated on the Open-Access Montreal Archive of Sleep Studies (MASS)
inferredcites →https://doi.org/10.48550/arxiv.1412.6980openalex-extracted
Adam: A Method for Stochastic Optimization
inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-extracted
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
inferredcites →https://doi.org/10.5665/sleep.1290openalex-extracted
Fast and Slow Spindles during the Sleep Slow Oscillation: Disparate Coalescence and Engagement in Memory Processing
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