Congratulations to our labmates and collaborators: Guohao Yu, Alina Zare, Weihuang Xu, Roser Matamala, Joel Reyes-Cabrera, Felix B. Fritschi and Thomas E. Juenger! Their paper, “Weakly Supervised Minirhizotron Image Segmentation with MIL-CAM” was recently accepted to the 16th European Conference… Read More
Tag: roots
WEAKLY SUPERVISED MINIRHIZOTRON IMAGE SEGMENTATION WITH MIL-CAM
Abstract: We present a multiple instance learning class activation map (MIL-CAM) approach for pixel-level minirhizotron image segmentation given weak image-level labels. Minirhizotrons are used to image plant roots in situ. Minirhizotron imagery is often composed of soil containing a few… Read More
UFII LECTURE SERIES: AI ADVANCES AND APPLICATIONS
In response to the recent AI initiative launched by the University of Florida, the UF Informatics Institute (UFII) is hosting a virtual seminar series, “AI Advances and Applications”. The online series will feature innovative work being conducted in AI and… Read More
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
ROOT IDENTIFICATION WITH MULTIPLE INSTANCE LEARNING PUBLISHED IN MACHINE VISION AND APPLICATIONS!
Congratulations to our labmates and collaborators Guohao Yu, Alina Zare, Hudanyun Sheng, Roser Matamala, Joel Reyes-Cabrera, Felix Fritschi and Thomas Juenger! Their paper, “Root Identification in Minirhizotron Imagery with Multiple Instance Learning”, was recently published in Machine Vision and Applications!… Read More
OVERCOMING SMALL DATASETS PUBLISHED IN COMPUTERS AND ELECTRONICS IN AGRICULTURE!
Congratulations 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… Read More
ROOT IDENTIFICATION WITH MULTIPLE INSTANCE LEARNING ACCEPTED TO MACHINE VISION AND APPLICATIONS!
Congratulations to our labmates Guohao Yu, Alina Zare and Hudanyun Sheng, as well as collaborators, Roser Matamala, Joel Reyes-Cabrera, Felix Fritschi and Thomas Juenger! Their paper, “Root Identification in Minirhizotron Imagery with Multiple Instance Learning”, was recently accepted to Machine… 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
OVERCOMING SMALL MINIRHIZOTRON DATASETS ACCEPTED TO COMPUTERS AND ELECTRONICS IN AGRICULTURE!
Congratulations 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… 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