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SUPER RESOLUTION FOR ROOT IMAGING PUBLISHED IN APPS!

August 2, 2020

Congratulations to our labmates Jose Ruiz-Munoz and Alina Zare as well as collaborators Jyothier Nimmagadda, Tyler Dowd and James Baciak!  Their paper, titled “Super Resolution for Root Imaging”, was recently published to Applications in Plant Sciences (APPS). If you’re interested in learning about a super-resolution framework for enhancing images of plant roots by using convolutional […]

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SUPER RESOLUTION FOR ROOT IMAGING ACCEPTED TO APPS!

May 8, 2020

Congratulations to our labmates Jose Ruiz-Munoz and Alina Zare as well as collaborators Jyothier Nimmagadda, Tyler Dowd and James Baciak!  Their paper, titled “Super Resolution for Root Imaging”, was recently accepted to Applications in Plant Sciences (APP). If you’re interested in learning about a super-resolution framework for enhancing images of plant roots by using convolutional […]

Read more: SUPER RESOLUTION FOR ROOT IMAGING ACCEPTED TO APPS! »

Super Resolution for Root Imaging

March 31, 2020

Abstract: High-resolution cameras have become very helpful for plant phenotyping by providing a mechanism for tasks such as target versus background discrimination, and the measurement and analysis of fine-above-ground plant attributes. However, the acquisition of high-resolution (HR) imagery of plant roots is more challenging than above-ground data collection. Thus, an effective super-resolution (SR) algorithm is […]

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