Deep learning for grape variety recognition
Bogdan Franczyk, Marcin Hernes, Adrianna Kozierkiewicz, Agata Kozina, Marcin Pietranik, Ingolf Roemer, Martin Schieck
Abstract
The production of food in an ecologically and economically sustainable manner is of significant importance today. Agricultural producers are increasingly being accompanied by elements of Agriculture 4.0 such as automation and decision-making support. This work shows an example of how the digitization of viticulture can be significantly supported by Deep Learning. The work presents an approach that can overcome the loss of human expertise in grape identification by using image-recognition-techniques and residual network architectures. Our developed model for grape identification at a vineyard reaches an accuracy of 99% of correctly recognized grape varieties.