My research focuses on leveraging artificial intelligence techniques, including among others computer vision and machine learning, to recognize traits in microscopic wood anatomy. My ultimate objective is to develop a wood identification pipeline to help facilitate wood identification, to combat illegal wood trade, and to support implementing (inter)national regulations. I also developed the EyeWood© microscopic wood database management system, and proposed the FEC method, a fast retrieval system for anatomical features based on machine learning.
Keywords
Wood Anatomy, Machine learning, Microscopic Image Classification, Feature Detection