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
Tag: plants
PLANTS MEET MACHINES PUBLISHED IN APPLICATIONS IN PLANT SCIENCES!
Congratulations to our labmates and collaborators Pamela S. Soltis, Gil Nelson, Alina Zare and Emily K. Meineke! They wrote the introduction for a special issue of Applicaitons in Plant Sciences. Their introduction is titled “Plants meet machines: Prospects in… Read More
PLANTS MEET MACHINES: PROSPECTS IN MACHINE LEARNING FOR PLANT BIOLOGY
Abstract: Machine learning approaches are affecting all aspects of modern society, from autocorrect applications on cell phones to self‐driving cars to facial recognition, personalized medicine, and precision agriculture. Although machine learning has a long history, drastic improvements in these application… 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
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
Peanut Maturity Classification using Hyperspectral Imagery
Abstract: Seed maturity in peanut ( Arachis hypogaea L.) determines economic return to a producer because of its impact on seed weight, and critically influences seed vigor and other quality characteristics. During seed development, the inner mesocarp layer of the… Read More
Cross-site learning in deep learning RGB tree crown detection
Abstract: Tree detection is a fundamental task in remote sensing for forestry and ecosystem ecology applications. While many individual tree segmentation algorithms have been proposed, the development and testing of these algorithms is typically site specific, with few methods evaluated… Read More
Breaking down barriers between remote sensing and plant pathology
Abstract: A critical component for enhancing productivity and quality of food and fiber is the ability to quickly detect and monitor plant diseases in order to prevent or minimize losses to agricultural and forest products (Mahlein 2016). The earlier (prior to… Read More