Abstract: Purpose: Root system architectures are complex, multidimensional, and challenging to characterize effectively for agronomic and ecological discovery. Methods: We propose a new method, Spatial and Texture Analysis of Root System architecture with Earth mover’s Distance (STARSEED), for comparing root… Read More
Tag: plants
CONGRATULATIONS TO XIAOLEI GUO FOR BECOMING A PHD CANDIDATE!
Congratulations to our labmate, Xiaolei Guo, for passing her Oral Qualifying Exam and becoming a PhD candidate! For the remainder of her PhD work, Xiaolei plans to investigate fundamental research questions on “Interactive Segmentation with Deep Metric Learning”. We are… Read More
ZARE PRESENTED IN UFII AI ADVANCES SEMINAR!
Dr. Alina Zare recently presented in the University of Florida Informatics Institute’s virtual seminar on AI Advances and Applications. During her talk, Alina discussed how the Machine Learning and Sensing Lab is using AI methods to advance the understanding… 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
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