Unlocking the Potential of Wind Energy with Machine Learning-Based Avian Detection: A Call to Action
This systematic literature review explores the potential of machine learning-based approaches to detect and prevent bird collisions with wind turbines. It provides a comprehensive review of the current approaches and identifies critical gaps in the literature, which may serve as the groundwork for f...
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Veröffentlicht in: | IEEE access 2023-01, Vol.11, p.1-1 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Online-Zugang: | Volltext |
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Zusammenfassung: | This systematic literature review explores the potential of machine learning-based approaches to detect and prevent bird collisions with wind turbines. It provides a comprehensive review of the current approaches and identifies critical gaps in the literature, which may serve as the groundwork for future research and development in this area. As a result, this work highlights the importance of inter- and transdisciplinary cooperations. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2023.3287861 |