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Highlight IDTitleStrategic Program Area(s)YearStation
Photo of
ID: 170
Centennial Edition, Wood Handbook—Wood as an Engineering Material

The Wood Handbook—Wood as an Engineering Material serves as a primary reference document for a wide variety of users-from the general publ ...

Principal Investigator : Alex C. Wiedenhoeft

Resource Management and Use2010FPL
Photo of (A) A representation of a deep neural network: the input to the neural network is an image of the transverse section of wood and the output is a confidence score over the woods on which the model was trained. (B) Conceptualizes the similarity of woods for a wood anatomist, showing which species are most likely to be confused with each other. (C) The results of the predictions of a model – the correct identification is shown in the rows, and the values in the cells are the proportion of all the images classified as the species listed in the columns, with the diagonal showing correct predictions.
ID: 1505
Machine Vision Wood Identification of Endangered Tropical Woods

Field identification of wood (screening) is the first step in a forensic workflow to combat illegal logging. Similarly, industries interested in ...

Principal Investigator : Alex C. Wiedenhoeft

Water, Air, and Soil
Resource Management and Use
2018FPL
Photo of The Xylotron uses machine-visioning technology to identify wood species. John Hermanson, USDA Forest Service
ID: 585
The Xylotron: A Field-Deployable Machine-Vision Wood Identification System

The Xylotron is a machine-vision-based wood identification system that uses a custom-designed wood imaging device (the Xyloscope), image analysi ...

Principal Investigator : Alex C. Wiedenhoeft

Resource Management and Use
Wildlife and Fish
Inventory and Monitoring
2014FPL