Carolin Fischer
Avdelingsleder/forskningssjef
Lenker
Linked inBiografi
Carolin has a Bachelor and Master in Forest Sciences and Wood technology from the Technical University (TU) in Munich.
She gained her PhD with the topic “Density and bending properties of Norway spruce structural timber – Inherent variability, site effects in machine strength grading and possibilities for presorting” in 2016 from the Norwegian University of Life Sciences (NMBU).
Carolin is the Head of Department for Forest Operations and Digitalisation at NIBIO. Her research work focuses on traceability along the forest value chain and wood quality evaluation early in the wood production chain. Her work includes also the coordination of SmartForest, a senter for research driven innovation (SFI), led by NIBIO.
Sammendrag
The European Union Deforestation Regulation (EUDR) mandates traceability of timber that makes up wood products from its harvest site to the end product to ensure sustainable wood sourcing. This study proposes a cost-effective, image-based method for tracing logs using alphabetic codes printed onto logs at the harvest site. These codes are detected and interpreted through a two-stage system leveraging deep learning models. The detection stage employs YOLOv8 to locate tracking codes in images of log piles. It is trained and evaluated on a dataset of 125 images, achieving an F1-score of 0.811 on unseen images. The recognition stage, trained on 1,020 images, uses YOLOv8 models to detect individual characters and their positions within each code. On a set of unseen images, the interpretation stage is able to identify 92.8% of the individual logs despite the limited quality of the printer and degradation of the codes due to stem wetness. Analysis indicates that errors predominantly arise in the character detection step. Compared to existing traceability approaches, this method is more cost-effective than RFID tags and attains higher accuracy than image-based biomarker tracking methods.
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