Tag: autoencoder
OVERCOMING SMALL DATASETS PUBLISHED IN COMPUTERS AND ELECTRONICS IN AGRICULTURE!
June 19, 2020Congratulations to our labmates, Weihuang Xu, Guohao Yu and Alina Zare, as well as collaborators Brenden Zurweller, Diane Rowland, Joel Reyes-Cabrera, Felix Fritschi, Roser Matamala and Thomas Juenger! Their paper, “Overcoming Small Minirhizotron Datasets Using Transfer Learning”, was published in Computers and Electronics in Agriculture. The document and code can be found here. Make sure […]
Read more: OVERCOMING SMALL DATASETS PUBLISHED IN COMPUTERS AND ELECTRONICS IN AGRICULTURE! »OVERCOMING SMALL MINIRHIZOTRON DATASETS ACCEPTED TO COMPUTERS AND ELECTRONICS IN AGRICULTURE!
April 28, 2020Congratulations to our labmates, Weihuang Xu, Guohao Yu and Alina Zare, as well as collaborators Brenden Zurweller, Diane Rowland, Joel Reyes-Cabrera, Felix Fritschi, Roser Matamala and Thomas Juenger! Their paper, titled “Overcoming Small Minirhizotron Datasets Using Transfer Learning”, was recently accepted to Computers and Electronics in Agriculture. Check it out here!
Read more: OVERCOMING SMALL MINIRHIZOTRON DATASETS ACCEPTED TO COMPUTERS AND ELECTRONICS IN AGRICULTURE! »Overcoming Small Minirhizotron Datasets Using Transfer Learning
March 22, 2019Abstract: Minirhizotron technology is widely used for studying the development of roots. Such systems collect visible-wavelength color imagery of plant roots in-situ by scanning an imaging system within a clear tube driven into the soil. Automated analysis of root systems could facilitate new scientific discoveries that would be critical to address the world’s pressing food, […]
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