Company Filing History:
Years Active: 2020
Title: Chris Mosbrucker: Innovator in Board Lumber Grading Technology
Introduction
Chris Mosbrucker is an accomplished inventor based in Philomath, OR (US). He has made significant contributions to the field of board lumber grading through innovative applications of deep learning techniques. With a total of 2 patents, Mosbrucker is recognized for his expertise in machine learning and its practical applications in industrial environments.
Latest Patents
Mosbrucker's latest patents focus on advanced methods for board lumber grading using deep learning semantic segmentation techniques. The first patent describes a method of board lumber grading performed in an industrial environment on a machine learning framework. This framework is configured as an interface to a machine learning-based deep convolutional network that is trained end-to-end, pixels-to-pixels on semantic segmentation. The method utilizes deep learning techniques to delineate board lumber characteristics, including their sizes and boundaries. The second patent reiterates this innovative approach, emphasizing the application of deep learning techniques in the same context.
Career Highlights
Chris Mosbrucker is currently employed at Lucidyne Technologies, Inc., where he continues to develop and refine his groundbreaking technologies. His work has positioned him as a leader in the integration of machine learning with traditional lumber grading processes.
Collaborations
Mosbrucker collaborates with talented individuals such as Revathy Priyanga Narasimhan and Patrick S Freeman, contributing to a dynamic and innovative work environment.
Conclusion
Chris Mosbrucker's contributions to board lumber grading through deep learning techniques highlight his role as a forward-thinking inventor. His patents reflect a commitment to advancing technology in the lumber industry, paving the way for more efficient grading processes.