معرفی
Dag Björnberg is a researcher at Linnaeus University, affiliated with the graduate school Data Intensive Applications (DIA) and the research groups Data Intensive Software Technologies and Applications (DISTA) and Linnaeus University Centre for Data Intensive Sciences and Applications.
His research focuses on applying artificial intelligence and machine learning techniques to solve challenges in the forest industry. Key projects include developing algorithms for log tracking using end-grain fingerprints, generating photorealistic log end images via conditional Generative Adversarial Networks (cGANs), and improving forest inventory efficiency through AI-driven methodologies.
- Doctoral project: Advanced identification methods for the forest industry via computer vision and AI
- ForestMap: Global forest mapping methodology
- Tree volume measurement by AI: Sweden-Brazil collaboration
His recent publications highlight the integration of GANs, image translation, and data-intensive approaches in forest resource management and AI development.