Explainable Artificial Intelligence (XAI) is gaining importance in various fields, including forestry and tree-growth modelling. However, challenges such as evaluating model interpretability, lack of transparency in some XAI methods, inconsistent terminology, and bias towards specific data types hinder its integration.In their article our colleagues Anahid Jalali, […]
Presentation given by our ecologist Anita Zolles (BWF) on the topic of AI for climate sensitive tree growth modeling. This scientific meeting was held in the week of April 17-21, 2023 in Palencia (Spain) to address Artificial Intelligence in the field of Ecosystem Management in its […]
Presentation given by our ecologist Anita Zolles (BWF) on the topic of AI for climate sensitive tree growth modeling. This scientific meeting was held in the week of April 17-21, 2023 in Palencia (Spain) to address Artificial Intelligence in the field of Ecosystem Management in its […]
The goal of the work package 6 is to develop machine learning prediction model for tree growth using a data centric paradigm to achieve a high performance AI-model on high-frequency tree growth data. Furthremore, we aim to develop a framework focusing on data quality improvement by […]