Unlocking the Potential of Wind Energy With Machine Learning-Based Avian Detection : A Call to Action

DOI zum Zitieren der Version auf EPub Bayreuth: https://doi.org/10.15495/EPub_UBT_00007598
URN to cite this document: urn:nbn:de:bvb:703-epub-7598-2

Title data

Principato, Marc ; Hasselwander, Lisa ; Stangner, Michael ; Büttner, Ricardo:
Unlocking the Potential of Wind Energy With Machine Learning-Based Avian Detection : A Call to Action.
In: IEEE Access. Vol. 11 (2023) . - pp. 64026-64048.
ISSN 2169-3536
DOI der Verlagsversion: https://doi.org/10.1109/ACCESS.2023.3287861

[thumbnail of Unlocking_the_Potential_of_Wind_Energy_With_Machine_Learning-Based_Avian_Detection_A_Call_to_Action.pdf]

Format:	PDF
Name:	Unlocking_the_Potential_of_Wind_Energy_With_Machine_Learning-Based_Avian_Detection_A_Call_to_Action.pdf
Version:	Published Version
Available under License	Creative Commons BY-NC-ND 4.0: Attribution, Noncommercial, No Derivative Works

Download (2MB)

Project information

Project title:	Project's official title Project's id Open Access Publizieren No information

Further data

Item Type:	Article in a journal
Keywords:	Energy management; Wind turbines; Wind energy; Machine learning; Renewable energy sources; Meteorology; Ecosystems; Machine learning; Energy conservation; Energy transition; environmental conservation; wind energy; machine learning
DDC Subjects:	000 Computer Science, information, general works > 004 Computer science 300 Social sciences > 330 Economics
Institutions of the University:	Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Former Professors > Chair Business Administration XVIII - Information Systems Management and Data Science - Univ.-Prof. Dr. Ricardo Büttner Faculties Faculties > Faculty of Law, Business and Economics Faculties > Faculty of Law, Business and Economics > Department of Business Administration Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XVIII - Information Systems Management and Data Science Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Former Professors
Language:	English
Originates at UBT:	Yes
URN:	urn:nbn:de:bvb:703-epub-7598-2
Date Deposited:	19 Mar 2024 10:20
Last Modified:	19 Mar 2024 10:21
URI:	https://epub.uni-bayreuth.de/id/eprint/7598

Download Statistics

Downloads

Downloads per month over past year