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A Deep Learning-Based Approach for the Detection of Infested Soybean Leaves

Title data

Farah, Niklas ; Drack, Nicolas ; Dawel, Hannah ; Büttner, Ricardo:
A Deep Learning-Based Approach for the Detection of Infested Soybean Leaves.
In: IEEE Access. Vol. 11 (2023) . - pp. 99670-99679.
ISSN 2169-3536
DOI: https://doi.org/10.1109/ACCESS.2023.3313978

Official URL: Volltext

Project information

Project title:
Project's official title
Project's id
Open Access Publizieren
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Project financing: Deutsche Forschungsgemeinschaft

Further data

Item Type: Article in a journal
Refereed: Yes
Keywords: Crops; Biological system modeling; Production; Pesticides; Economics; Deep learning; Autonomous aerial vehicles; Convolutional neural networks; Plants (biology); Plant diseases; Convolutional neural network; VGG-19; plant infestation; soybean; Diabrotica speciosa; caterpillars
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration > Chair Business Administration XVIII - Information Systems Management and Data Science > 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
Result of work at the UBT: Yes
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 23 Mar 2024 22:00
Last Modified: 25 Mar 2024 06:49
URI: https://eref.uni-bayreuth.de/id/eprint/89005