{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/learning-robust-features-using-deep-learning","title":"Learning Robust Features using Deep Learning for Automatic Seizure Detection","arxiv_id":"1608.00220","date":"2016-07-31","proceeding":null,"authors":["Pierre Thodoroff","Joelle Pineau","Andrew Lim"],"abstract":"We present and evaluate the capacity of a deep neural network to learn robust\nfeatures from EEG to automatically detect seizures. This is a challenging\nproblem because seizure manifestations on EEG are extremely variable both\ninter- and intra-patient. By simultaneously capturing spectral, temporal and\nspatial information our recurrent convolutional neural network learns a general\nspatially invariant representation of a seizure. The proposed approach exceeds\nsignificantly previous results obtained on cross-patient classifiers both in\nterms of sensitivity and false positive rate. Furthermore, our model proves to\nbe robust to missing channel and variable electrode montage.","url_abs":"http://arxiv.org/abs/1608.00220v1","url_pdf":"http://arxiv.org/pdf/1608.00220v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"learning-robust-features-using-deep-learning","repo_url":"https://github.com/Sharad24/Epileptic-Seizure-Detection","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"deep-learning","task_name":"Deep Learning"},{"task_slug":"eeg-1","task_name":"EEG"},{"task_slug":"eeg","task_name":"Electroencephalogram (EEG)"},{"task_slug":"seizure-detection","task_name":"Seizure Detection"},{"task_slug":"sensitivity","task_name":"Sensitivity"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1608.00220","atlas_url":"https://app.syntology.ai/?focus=1608.00220","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}