Category: News

Dr. Alina Zare recently presented as a keynote speaker at the Phenome 2020 conference in Tucson, AZ! The Phenome conference is a gathering of a multidisciplinary community comprising plant biologists, ecologists, engineers, agronomists, computational scientists, and representatives from U.S. federal agencies which is focused on the methodologies and technologies that enable the study of plant […]

Congratulations to Gatorsense alumnas Hudanyun Sheng for accepting a research position at the Donald Danforth Plant Science Center in St. Louis, MO! We can’t wait to see all of the exciting things you do, Hudanyun!

The Machine Learning and Sensing Lab is excited to welcome our newest lab member, Jason Chen! Jason is a third year Computer Science major at the University of Florida who will be working on new hardware and software for monitoring insect bioacoustics. Additionally, Jason will be investigating new opportunities for public outreach. Welcome to our […]

Machine Learning and Sensing Lab collaborators Ben Weinstein, Sergio Marconi, Stephanie Bohlman, Alina Zare and Ethan White recently had a paper accepted to Ecological Informatics!   The paper discusses the utilization of data from multiple sites to train generalized tree-crown detectors.  Check it out here!

Machine Learning and Sensing Lab Alumni, Anand Seethepalli, and collaborators recently had a paper accepted to Plant Phenomics.  The article discusses an innovative platform to help collect consistent images of root crowns for phenotyping.  Check it out here! 

Understanding and managing forests is crucial to understanding and potentially mitigating the effects of climate change, invasive species, and shifting land use on natural systems and human society. However, collecting data on individual trees in the field is expensive and time consuming, which limits the scales at which this crucial data is collected. Remotely sensed […]

Abstract: The spectral signatures of the materials contained in hyperspectral images (HI), also called endmembers (EM), can be significantly affected by variations in atmospheric, illumination or environmental conditions typically occurring within an HI. Traditional spectral unmixing (SU) algorithms neglect the spectral variability of the endmembers, what propagates significant mismodeling errors throughout the whole unmixing process […]

Our labmate, Dylan Stewart, recently accepted an internship offer from the Naval Surface Warfare Center in Panama City Beach, FL.  Dylan has been researching image registration approaches for use in both underwater and aerial scene understanding.  During his internship, Dylan will get to apply his research to a variety of new, exciting problems and datasets! […]

The Machine Learning and Sensing Lab was recently featured by UF ECE!  Their article featured the lab’s collaboration with agricultural researchers at the UF Beef Research Unit.  Check out what our labmate, Dylan Stewart, is working on in the full story, here.

Congratulations to Tyler Kim on his acceptance to Columbia University!  Tyler spent summer 2019 participating as a high school student in the UF Student Science Training Program (SSTP).   During this time, Tyler conducted research on texture analysis using artificial neural networks and was awarded “best paper” at the program’s closing ceremony.  Tyler will major in […]