20.500.12556/DiRROS-30071 Evaluation of deep learning models for image-based classification of timber logs by market value The identification of standing tree species, timber logs, and on-site assessment of their quality and value using images holds significant potential for forestry applications, including inventory management, traceability under EU regulations like the Deforestation Regulation, and market valuation amid growing demands for sustainable practices. This study addresses this by classifying images of timber logs by tree species and market value using the Orange data mining software, which leverages pre-trained convolutional neural networks (Inception v3 and SqueezeNet) to generate embeddings from a dataset of 5549 images collected at a real timber auction in Slovenia, followed by logistic regression image classification. Results show high accuracy for tree species classification (up to 92.6%), but substantially lower accuracy for market value classification (40%–55%), reflecting the greater complexity of value determination from visual features. These findings underscore the promise of deep learning for species identification while indicating the need for further methodological advancements to enhance value classification reliability, which offers the practical impact for operational forestry and bioeconomy value chains. image classification timber quality high value assortments auctions wood products convolutional neural networks CNNs non-destructive evaluation machine learning in forestry tree species image recognition forest wood assortment value klasifikacija slik kakovost lesa visokovredni sortimenti dražbe lesni izdelki konvolucijske nevronske mreže CNN nedestruktivno vrednotenje strojno učenje v gozdarstvu prepoznavanje slik drevesnih vrst vrednost gozdnega lesnega sortimenta true false true Angleški jezik Slovenski jezik Znanstveno delo 2026-06-12 15:05:23 2026-06-12 15:05:23 2026-06-13 03:52:18 0000-00-00 00:00:00 2026 0 0 Nasl. z nasl. zaslona; Opis vira z dne 12. 6. 2026; str. 1-15 iss. 5, [article no.] 518 Vol. 17 2026 0000-00-00 Zaloznikova Objavljeno NiDoloceno 0000-00-00 0000-00-00 0000-00-00 630*7 1999-4907 10.3390/f17050518 281502723 https://www.mdpi.com/1999-4907/17/5/518 1 6072a72b-665f-11f1-aebd-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=45374 forests-17-00518.pdf forests-17-00518.pdf 1 1DD0C7041CC424F06263C22D47AFF197 3e392f52402c30ac92d6e9aad2c5a3b02edc47453953d7b688071d1367cc071f 7acac610-665f-11f1-aebd-001a4af901a5 https://dirros.openscience.si/Dokument.php?lang=slv&id=45375 Gozdarski inštitut Slovenije 0 0 0