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Detection of Colchicum autumnale in drone images, using a machine-learning approach

  • Colchicum autumnale are toxic autumn-blooming flowering plants, which often grow on extensive meadows and pastures. Thus, they pose a threat to farm animals especially in hay and silage. IntensiveColchicum autumnale are toxic autumn-blooming flowering plants, which often grow on extensive meadows and pastures. Thus, they pose a threat to farm animals especially in hay and silage. Intensive grassland management or the use of herbicides could reduce these weeds but environment protection requirements often prohibit these measures. For this reason, a non-chemical site- or plant-specific weed control is sought, which aims only at a small area around the C. autumnale and with low impact on the surrounding flora and fauna. For this purpose, however, the exact locations of the plants must be known. In the present paper, a procedure to locate blooming C. autumnale in high-resolution drone images in the visible light range is presented. This approach relies on convolutional neural networks to detect the flower positions. The training data, which is based on hand-labeled images, is further enhanced through image augmentation. The quality of the detection was evaluated in particular for grassland sites which were not included in the training to get an estimate for how well the detector works on previously unseen sites. In this case, 88.6% of the flowers in the test dataset were detected, which makes it suitable, e.g., for applications where the training is performed by the manufacturer of an automatic treatment tool and where the practitioners apply it to their previously unseen grassland sites.show moreshow less

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Metadaten
Author:Lukas PetrichORCiD, Georg Lohrmann, Matthias Neumann, Fabio Martin, Andreas Frey, Albert Stoll, Volker Schmidt
DOI:https://doi.org/10.1007/s11119-020-09721-7
ISSN/eISSN:1385-2256
Parent Title (English):Precision Agriculture
Publisher:Springer
Document Type:Article
Language:English
Date of Publication (online):2020/05/06
Publishing Institution:Hochschule Nürtingen-Geislingen
Release Date:2023/03/24
Tag:Colchicum autumnale; Convolutional neural network; Drone image; Object detection
Volume:21
Issue:6
Page Number:13
First Page:1291
Last Page:1303
Institutes:Fakultät Agrarwirtschaft, Volkswirtschaft und Management
open access:ja
Licence (German):License LogoCreative Commons - CC BY - Namensnennung 4.0 International