Deep Learning Vision in Agriculture

Aug. 12, 2024

Learn how the LaserWeeder’s advanced computer vision system and AI deep learning models promote sustainable agricultural practices while differentiating weeds from crops in real-time.

Sharon Spielman

Related To: Carbon Robotics

In this second of a two-part series, Paul Mikesell, CEO of Carbon Robotics, explains to the Machine Design audience how the vision system on the company’s laser weeding machine works. From the training of AI models to real-time processing to differentiating “ugly” produce from saleable crops, Mikesell walks us through the LaserWeeder’s capabilities.

He also touches on the integration of deep learning with mechanical components, the assurance that the lasers are stable on the moving unit, safety measures to prevent fires and what a cost-benefit analysis would look like for a farmer.

Watch Part 1 of this interview series with Paul Mikesell

About the Author

Sharon Spielman | Technical Editor, Machine Design

As Machine Design’s technical editor, Sharon Spielman produces content for the brand’s focus audience—design and multidisciplinary engineers. Her beat includes 3D printing/CAD; mechanical and motion systems, with an emphasis on pneumatics and linear motion; automation; robotics; and CNC machining.

Spielman has more than three decades of experience as a writer and editor for a range of B2B brands, including those that cover machine design; electrical design and manufacturing; interconnection technology; food and beverage manufacturing; process heating and cooling; finishing; and package converting.

Email: [email protected]

LinkedIn: @sharonspielman

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