Second edition of the Deep Learning for Forestry Course successfully finalised

The second edition of the "Deep Learning for Forestry" course, hosted by the University of Groningen, was a great success. Held online with weekly online sessions from January 15 to February 24 2024, and with an on-site week in Groningen from March 17-22, this blended intensive programme (BIP) equipped students with cutting-edge skills in AI and deep learning. Participants worked with Python, TensorFlow Keras, and advanced neural network techniques to analyse satellite and UAV data. Meanwhile, they used these tools to take a closer look at forestry (differentiating tree species and detecting game damage). This unique learning experience brought together students from 6 ENLIGHT partner universities from different disciplines, allowing them to develop their teamwork and intercultural skills as well. 

Below are a few quotes of the course lecturers:

Matias Valdenegro Toro , University of Groningen

Teacher & Coordinator

"As Coordinator of this course, it was very nice to see Zoom squares on the screen transform into real people, and then we could experience Forestry, Machine Learning, and Data Science together, but not only technical topics, also we enjoyed food and intercultural development. Students teamed up across institutional boundaries to start a small project, and via this challenge they learned a broad set of topics.

We had students from many Enlight partner Universities, mainly from Göttingen, Groningen, and Bordeaux, but also from Galway, Ghent, and Tartu. Each student brought they perspective into the course, and learned about different topics. Groningen students learned about Forestry, Göttingen students learned about Data Science, and Bordeaux students learned about Deep Learning.

I am very happy how the in-person part went and I look forward to see the final project reports from student groups!"

Lutz Fehrmann , University of Göttingen

Teacher

"From my perspective the most important and interesting part of this activity is to see how students from different disciplines (Forest Science, Computer Science, Artificial Intelligence) are working together and help each other to get insights in their very special domains. They are confronted to new concepts and questions that they cannot solve in their own discipline alone, but are forced to leave their comfort zone and work together in a multicultural setting.

Students from forest science and forest ecology get insights into the application of machine learning techniques, while students in artificial intelligence learn about the importance of understanding and interpreting the data and example applications from forestry and remote sensing. Beside the subject matter questions and learning outcomes of this course, the intercultural component and team building helps students to increase important soft skills that they need for their future careers."