Matches in Data.gov.be for { <http://data.gov.be/.well-known/genid/dataset/ucl/doi-10-14428/DVN/E7AISH> ?p ?o ?g. }
Showing items 1 to 25 of
25
with 100 items per page.
- E7AISH accessRights PUBLIC @default.
- E7AISH bibliographicCitation "Langlois, Quentin, 2025, "BIOSIGNALS 2025", https://doi.org/10.14428/DVN/E7AISH, Open Data @ UCLouvain, V1" @default.
- E7AISH created "2025-02-13T12:48:55Z" @default.
- E7AISH creator 83c74b72b51e3e645d68196aeebd2a58474d7f66 @default.
- E7AISH description "Begleitdaten zum Paper "Comparison between Machine Learning and Deep Learning on Multiple Motor Imagery Paradigms in a Low-Resource Context" (BIOSTEC BIOSIGNALS 2025). Schauen Sie sich das zugehörige GitHub-Repository an: https://forge.uclouvain.be/QuentinLanglois/biosignals-2025-vergleich-ml-und-dl-für-motorische-Bilder/" @default.
- E7AISH description "Companion data to the paper "Comparison between Machine Learning and Deep Learning on Multiple Motor Imagery Paradigms in a Low-Resource Context" (BIOSTEC BIOSIGNALS 2025). Bekijk de bijbehorende GitHub repository: https://forge.uclouvain.be/QuentinLanglois/biosignals-2025-comparison-ml-and-dl-for-motor-imagery/" @default.
- E7AISH description "Companion data to the paper "Comparison between Machine Learning and Deep Learning on Multiple Motor Imagery Paradigms in a Low-Resource Context" (BIOSTEC BIOSIGNALS 2025). Check out the associated GitHub repository: https://forge.uclouvain.be/QuentinLanglois/biosignals-2025-comparison-ml-and-dl-for-motor-imagery/" @default.
- E7AISH description "Données complémentaires à l'article "Comparaison entre l'apprentissage automatique et l'apprentissage profond sur plusieurs paradigmes d'imagerie motrice dans un contexte de faibles ressources" (BIOSTEC BIOSIGNALS 2025). Consultez le référentiel GitHub associé: https://forge.uclouvain.be/QuentinLanglois/biosignals-2025-comparison-ml-and-dl-for-motor-imagery/" @default.
- E7AISH identifier "doi:10.14428/DVN/E7AISH" @default.
- E7AISH issued "2025-02-14T10:46:08Z" @default.
- E7AISH language ENG @default.
- E7AISH modified "2025-02-14T10:46:08Z" @default.
- E7AISH publisher 0419052272 @default.
- E7AISH subject "Computer and Information Science" @default.
- E7AISH subject "Medicine, Health and Life Sciences" @default.
- E7AISH title "BIOSIGNALS 2025" @default.
- E7AISH title "BIOSIGNALS 2025" @default.
- E7AISH title "BIOSIGNALS 2025" @default.
- E7AISH title "BIOSIGNALS 2025" @default.
- E7AISH type Dataset @default.
- E7AISH contactPoint genid69130 @default.
- E7AISH landingPage E7AISH @default.
- E7AISH theme HEAL @default.
- E7AISH theme TECH @default.
- E7AISH version "1" @default.