| Title: | Vine Leaf Disease and AI, Detection of grapevine leaf diseases based on RGB-images, deep learning and its integration in a mobile application |
| Authors: |
Licka, Maria-Theresa, Elisabeth-von-Thadden-Schule, Heidelberg Schweikert, Mario, Leibniz-Gymnasium, Neustadt an der Weinstraße |
| Contributors: | Editor: Physikalisch-Technische Bundesanstalt (PTB), ISNI: 0000 0001 2186 1887 HostingInstitution: Physikalisch-Technische Bundesanstalt (PTB), ISNI: 0000 0001 2186 1887 |
| Pages: | 16 |
| Language: | en |
| DOI: | 10.7795/320.202210 |
| Resource Type: | Text / Article |
| Publisher: | Physikalisch-Technische Bundesanstalt (PTB) |
| Rights: | Vervielfältigung nur zum eigenen persönlichen Gebrauch. |
| Dates: |
Available: 2023-03-16 Accepted: 2022-06-20 Submitted: 2022-02-04 |
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| Keywords: | Grapevine leaf ; Disease ; Smartphone App ; Machine learning ; Convolutional Neural Network ; Python ; Tensorflow ; Pesticide usage ; Agriculture ; Sustainability |
| Abstract: | This project enables early grapevine leaf disease identification on grape leaves by cell phone images, thereby allowing a precise usage of pesticides. The application is based on artificial intelligence (AI) which is trained to detect and differentiate the most common diseases. A continuous update of the extent and geographical location of disease spreading gives further valuable information to the winemakers using the application. |
| Series Information: | Junge Wissenschaft. Paper 10/2022 |
| Other: | In der Jungen Wissenschaft werden Forschungsarbeiten von Schüler/innen, die selbstständig, z.B. in einer Schule oder einem Schülerforschungszentrum, durchgeführt wurden, veröffentlicht. |
| Citation: | Licka, Maria-Theresa ; Schweikert, Mario . Vine Leaf Disease and AI. Detection of grapevine leaf diseases based on RGB-images, deep learning and its integration in a mobile application. Physikalisch-Technische Bundesanstalt (PTB), 2022. DOI: https://doi.org/10.7795/320.202210 |