Cover Image

EEG Artifact Detection and Correction with Deep Autoencoders

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Aquilué-Llorens, David, Soria-Frisch, Aureli
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Deep Autoencoders for Unsupervised Anomaly Detection in Wildfire Prediction
by: Üstek, İrem, et al.
Published: (2024)

Image-based Data Representations of Time Series: A Comparative Analysis in EEG Artifact Detection
by: Maiwald, Aaron, et al.
Published: (2023)

TransformEEG: Towards Improving Model Generalizability in Deep Learning-based EEG Parkinson's Disease Detection
by: Del Pup, Federico, et al.
Published: (2025)

Pre-Training Graph Contrastive Masked Autoencoders are Strong Distillers for EEG
by: Wei, Xinxu, et al.
Published: (2024)

Adversarial Artifact Detection in EEG-Based Brain-Computer Interfaces
by: Chen, Xiaoqing, et al.
Published: (2022)

Anomaly Correction of Business Processes Using Transformer Autoencoder
by: Gong, Ziyou, et al.
Published: (2024)

Autoencoders for Anomaly Detection are Unreliable
by: Bouman, Roel, et al.
Published: (2025)

ZUNA: Flexible EEG Superresolution with Position-Aware Diffusion Autoencoders
by: Warner, Christopher, et al.
Published: (2026)

The Deep-Match Framework for Event-Related Potential Detection in EEG
by: Zylinski, Marek, et al.
Published: (2026)

Are Sparse Autoencoder Benchmarks Reliable?
by: Chanin, David
Published: (2026)

Survey on Plagiarism Detection in Large Language Models: The Impact of ChatGPT and Gemini on Academic Integrity
by: Pudasaini, Shushanta, et al.
Published: (2024)

Sparse Autoencoders, Again?
by: Lu, Yin, et al.
Published: (2025)

An Introductory Survey to Autoencoder-based Deep Clustering -- Sandboxes for Combining Clustering with Deep Learning
by: Leiber, Collin, et al.
Published: (2025)

Autoencoding Random Forests
by: Vu, Binh Duc, et al.
Published: (2025)

Detecting Generative Parroting through Overfitting Masked Autoencoders
by: Taghanaki, Saeid Asgari, et al.
Published: (2024)

ArtifactLens: Hundreds of Labels Are Enough for Artifact Detection with VLMs
by: Burgess, James, et al.
Published: (2026)

Real-time Noise Detection and Classification in Single-Channel EEG: A Lightweight Machine Learning Approach for EMG, White Noise, and EOG Artifacts
by: Enshaei, Hossein, et al.
Published: (2025)

Enhancing Fairness in Autoencoders for Node-Level Graph Anomaly Detection
by: Wang, Shouju, et al.
Published: (2025)

Data Whitening Improves Sparse Autoencoder Learning
by: Saraswatula, Ashwin, et al.
Published: (2025)

Hybrid Autoencoder-Based Framework for Early Fault Detection in Wind Turbines
by: Nair, Rekha R, et al.
Published: (2025)

Variational Autoencoders for P-wave Detection on Strong Motion Earthquake Spectrograms
by: Ispak, Turkan Simge, et al.
Published: (2026)

Hybrid Quantum Deep Learning Model for Emotion Detection using raw EEG Signal Analysis
by: Chandanwala, Ali Asgar, et al.
Published: (2024)

Multi-scale Masked Autoencoder for Electrocardiogram Anomaly Detection
by: Zhou, Ya, et al.
Published: (2025)

Drift-Aware Variational Autoencoder-based Anomaly Detection with Two-level Ensembling
by: Li, Jin, et al.
Published: (2026)

A Real-time Anomaly Detection Using Convolutional Autoencoder with Dynamic Threshold
by: Maitra, Sarit, et al.
Published: (2024)

Accuracy-Constrained CNN Pruning for Efficient and Reliable EEG-Based Seizure Detection
by: K, Mounvik, et al.
Published: (2025)

GEPD:GAN-Enhanced Generalizable Model for EEG-Based Detection of Parkinson's Disease
by: Zhang, Qian, et al.
Published: (2025)

Subliminal Learning is a LoRA Artifact
by: Nief, Todd, et al.
Published: (2026)

Beyond Augmentation: Score-Guided Pathological Prior for EEG-based Depression Detection
by: Chen, Xiaojing, et al.
Published: (2026)

Product-Aware Deep Autoencoders for Robust Process Monitoring in Multi-Product Cyber-Physical Systems
by: Islam, MD Shafikul, et al.
Published: (2026)

EEG-Bench: A Benchmark for EEG Foundation Models in Clinical Applications
by: Kastrati, Ard, et al.
Published: (2025)

GRASPED: Graph Anomaly Detection using Autoencoder with Spectral Encoder and Decoder (Full Version)
by: Choong, Wei Herng, et al.
Published: (2025)

MCLPD:Multi-view Contrastive Learning for EEG-based PD Detection Across Datasets
by: Zhang, Qian, et al.
Published: (2025)

Large EEG-U-Transformer for Time-Step Level Detection Without Pre-Training
by: Wu, Kerui, et al.
Published: (2025)

Amplifying Pathological Detection in EEG Signaling Pathways through Cross-Dataset Transfer Learning
by: Darvishi-Bayazi, Mohammad-Javad, et al.
Published: (2023)

SynthSAEBench: Evaluating Sparse Autoencoders on Scalable Realistic Synthetic Data
by: Chanin, David, et al.
Published: (2026)

Bidirectional Variational Autoencoders
by: Kosko, Bart, et al.
Published: (2025)

Manifold-Matching Autoencoders
by: Cheret, Laurent, et al.
Published: (2026)

Hybrid Deep Convolutional Neural Networks Combined with Autoencoders And Augmented Data To Predict The Look-Up Table 2006
by: Djeddou, Messaoud, et al.
Published: (2024)

Spatiotemporal EEG-Based Emotion Recognition Using SAM Ratings from Serious Games with Hybrid Deep Learning
by: Rehman, Abdul, et al.
Published: (2025)