| DOI | Trouver le DOI : https://doi.org/10.1109/ICMLA61862.2024.00269 |
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| Auteur | Rechercher : Ebadi, Ashkan1Identifiant ORCID : https://orcid.org/0000-0002-4542-9105; Rechercher : Auger, Alain; Rechercher : Gauthier, Yvan1 |
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| Affiliation | - Conseil national de recherches Canada. Technologies numériques
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| Format | Texte, Article |
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| Conférence | 2024 International Conference on Machine Learning and Applications, ICMLA, December 18 - 20, 2024, Miami, Florida, United States |
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| Sujet | emerging technologies; future signals; burst detection; machine learning; underwater sensing |
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| Résumé | Detecting emerging technologies is crucial as it enables industries and policymakers to anticipate future trends, allocate resources efficiently, and foster innovation. Research plays a pivotal role in developing and advancing emerging technologies, driving innovation and shaping the trajectory of future technological landscapes. In this work, inspired by stock market analysis and leveraging machine learning, we analyze three decades of scientific publications in the field of underwater sensing, as the case technology, to identify bursty terms. We also employ historical data to develop a classifier predicting their future popularity trends. |
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| Date de publication | 2024-12-18 |
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| Maison d’édition | IEEE |
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| Dans | |
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| Langue | anglais |
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| Publications évaluées par des pairs | Oui |
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| Exporter la notice | Exporter en format RIS |
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| Signaler une correction | Signaler une correction (s'ouvre dans un nouvel onglet) |
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| Identificateur de l’enregistrement | 9de089de-5e5e-4e94-bf4e-22f4f634d74f |
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| Enregistrement créé | 2025-03-12 |
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| Enregistrement modifié | 2025-03-18 |
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