METHOD OF BOARD LUMBER GRADING USING DEEP LEARNING TECHNIQUES

A method of board lumber (Table 2) grading is performed in an industrial environment on a machine learning framework (12) configured as an interface to a machine learning-based deep convolutional network (20) that is trained end-to-end, pixels-to-pixels on semantic segmentation. The method uses deep...

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Bibliographische Detailangaben
Hauptverfasser:	Johnsrude, Kevin, Mosbrucker, Chris, Mortensen, Eric N, Robin, Dan, Weintraub, Joseph H, Aronson, Hayden Michael, Shear, Ryan T, Freeman, Patrick, Narasimhan, Revathy
Format:	Patent
Sprache:	eng
Schlagworte:	CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING HANDLING RECORD CARRIERS IMAGE DATA PROCESSING OR GENERATION, IN GENERAL INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIRCHEMICAL OR PHYSICAL PROPERTIES MEASURING PHYSICS PRESENTATION OF DATA RECOGNITION OF DATA RECORD CARRIERS TESTING
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Beschreibung
Zusammenfassung:	A method of board lumber (Table 2) grading is performed in an industrial environment on a machine learning framework (12) configured as an interface to a machine learning-based deep convolutional network (20) that is trained end-to-end, pixels-to-pixels on semantic segmentation. The method uses deep learning techniques that are applied to semantic segmentation to delineate board lumber characteristics (Table 1), including their sizes and boundaries.