Abstract: Generative adversarial networks (GANs) have shown tremendous promise in learning to generate data and effective at aiding semi-supervised classification. However, to this point, semi-supervised GAN methods make the assumption that the unlabeled data set contains only samples of the… Read More
Tag: gan
SUPER RESOLUTION FOR ROOT IMAGING PUBLISHED IN APPS!
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… Read More
SUPER RESOLUTION FOR ROOT IMAGING ACCEPTED TO APPS!
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… Read More
Super Resolution for Root Imaging
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… Read More