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Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods

Author(s):

Prabu Ravindran
Frank C. Owens
Adam C. Wade
Rubin Shmulsky

Year:

2022

Publication type:

Scientific Journal (JRNL)

Primary Station(s):

Forest Products Laboratory

Source:

Frontiers in Plant Science journal

Description

Availability of and access to wood identification expertise or technology is a critical component for the design and implementation of practical, enforceable strategies for effective promotion, monitoring and incentivisation of sustainable practices and conservation efforts in the forest products value chain. To address this need in the context of the multi-billion-dollar North American wood products industry 22-class, image-based, deep learning models for the macroscopic identification of North American diffuse porous hardwoods were trained for deployment on the open-source, field-deployable XyloTron platform using transverse surface images of specimens from three different xylaria and evaluated on specimens from a fourth xylarium that did not contribute training data. Analysis of the model performance, in the context of the anatomy of the woods considered, demonstrates immediate readiness of the technology developed herein for field testing in a human-in-the-loop monitoring scenario. Also proposed are strategies for training, evaluating, and advancing the state-of-the-art for developing an expansive, continental scale model for all the North American hardwoods.

Citation

Ravindran, Prabu; Owens, Frank C.; Wade, Adam C.; Shmulsky, Rubin; Wiedenhoeft, Alex C. 2022. Towards Sustainable North American Wood Product Value Chains, Part I: Computer Vision Identification of Diffuse Porous Hardwoods. Frontiers in Plant Science. 12: 104536. https://doi.org/10.3389/fpls.2021.758455.

Cited

Publication Notes

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  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.
https://www.fs.usda.gov/treesearch/pubs/64293