mlsanityData to 7 Oct 2026

Learning Robust Features using Deep Learning for Automatic Seizure Detection

arXiv 1608.00220 ↗First posted 31 Jul 2016cs.LG cs.CVcited by 16

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Abstract (arXiv)

We present and evaluate the capacity of a deep neural network to learn robust features from EEG to automatically detect seizures. This is a challenging problem because seizure manifestations on EEG are extremely variable both inter- and intra-patient. By simultaneously capturing spectral, temporal and spatial information our recurrent convolutional neural network learns a general spatially invariant representation of a seizure. The proposed approach exceeds significantly previous results obtained on cross-patient classifiers both in terms of sensitivity and false positive rate. Furthermore, our model proves to be robust to missing channel and variable electrode montage.

Key facts. Cited by 16 papers in the map (data through 7 Oct 2026). First posted on arXiv 31 Jul 2016.

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Citing papers per year: 2021: 4; 2022: 1; 2023: 2; 2024: 3; 2025: 5; 2026: 1.

16 papers.

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  1. 2021Robust learning from corrupted EEG with dynamic spatial filteringcited by 14
  2. 2024REST: Efficient and Accelerated EEG Seizure Analysis through Residual State Updatescited by 11
  3. 2023VSViG: Real-time Video-based Seizure Detection via Skeleton-based Spatiotemporal ViGcited by 5
  4. 2024SWIM: Short-Window CNN Integrated with Mamba for EEG-Based Auditory Spatial Attention Decodingcited by 4
  5. 2021Automated Detection of Abnormalities from an EEG Recording of Epilepsy Patients With a Compact Convolutional Neural Networkcited by 3
  6. 2021An overview of deep learning techniques for epileptic seizures detection and prediction based on neuroimaging modalities: Methods, challenges, and future workscited by 3
  7. 2025Deep Learning-Powered Electrical Brain Signals Analysis: Advancing Neurological Diagnosticscited by 3
  8. 2021Deep Cellular Recurrent Network for Efficient Analysis of Time-Series Data with Spatial Informationcited by 2
  9. 2022EEG-based Image Feature Extraction for Visual Classification using Deep Learningcited by 2
  10. 2023Optimized preprocessing and Tiny ML for Attention State Classificationcited by 1
  11. 2025SeizureFormer: A Transformer Model for IEA-Based Seizure Risk Forecastingcited by 1
  12. 2025EEG-Based Inter-Patient Epileptic Seizure Detection Combining Domain Adversarial Training with CNN-BiLSTM Networkcited by 1
4 more
  1. 2024Using Explainable AI for EEG-based Reduced Montage Neonatal Seizure Detectioncited by 0
  2. 2025Optimizing Speech Multi-View Feature Fusion through Conditional Computationcited by 0
  3. 2025MT-NAM: An Efficient and Adaptive Model for Epileptic Seizure Detectioncited by 0
  4. 2026LookAroundNet: Extending Temporal Context with Transformers for Clinically Viable EEG Seizure Detectioncited by 0