Artificial Intelligence and Forensic Wood Identification Stories
MSU researchers use AI to better evaluate lumber
Researchers in the Forest and Wildlife Research Center hope to leverage artificial intelligence to improve grading technology for soft and hardwoods. The machine learning method will augment existing grading technology. The team will develop an image-based machine learning model that will be able to tease out nuanced differences in lumber characteristics, such as knots and decay. In certain circumstances, these characteristics can be a challenge for current automated and human grading technologies and techniques. Since the value of each piece of lumber value is closely related to the nature and extent of these characteristics, researchers hope the tool will help the forest products industry increase profitability.