AgriAI program

All times are in the Central European Summer Time (CEST, UTC+2) timezone.

September 20, 2023 (Wednesday), 09:00-11:00, room 106

09:00–09:15	Massimo Martinelli Welcome Session
09:15–09:35	Qiang Huang, YouZhi Tao, Shitao Ding, Yongbo Liu and Francesco Mariniello Automatic Construction of Knowledge Graph of Tea Diseases and Pests
09:35–09:55	Paolo Bertellini, Gianluca D’Addese and Giorgia Franchini Binary Classification of Agricultural Crops Using Sentinel Satellite Data and Machine Learning Techniques
09:55–10:15	Justyna Stypułkowska The Use of AI to Determine the Condition of Corn in a Field Robot that Meets the Requirements of Precision Farming
10:15–10:35	Naeem Iqbal, Christoph Manss, Christian Scholz, Daniel Koenig, Matthias Igelbrink and Arno Ruckelshausen AI-based Maize and Weeds Detection on the Edge with CornWeed Dataset
10:35–10:55	Giovanna Castellano, Pasquale De Marinis and Gennaro Vessio Applying Knowledge Distillation to Improve Weed Mapping With Drones

11:30–11:50	Gábor Hartyányi and Laszlo Czuni Recognition of Weeds in Cornfields
11:50–12:10	Yaru Zhang, Arif Yilmaz, Mirela Popa and Christopher Brewster Analysis of the Impact of Data Augmentation on the Performance of Deep Learning Models in Multispectral Food Authenticity Identification
12:10–12:30	Szilárd Molnár and Levente Tamás Segmentation Methods Evaluation on Grapevine Leaf Diseases
12:30–12:50	Lyudmyla Kuzmych, Halyna Voropai and Stepan Kuzmych Mathematical Modeling of Water Regimes on Drained Lands
12:50–13:10	Antonio Bruno, Davide Moroni and Massimo Martinelli Efficient Deep Learning Approach for Olive Disease Classification
13:10–13:20	AgriAI BEST PAPERS AWARDS
13:20–13:30	Davide Moroni Closing session