Category: News

The Machine Learning and Sensing Lab is excited to welcome Khaled Hamad as a new Ph.D. student! Khaled received his MS degree in Electrical & Computer Engineering from the University of Florida in August 2021. He recently presented a new Machine Learning prediction model for Cyber-Physical Security for Smart Grid, and submitted his paper for the […]

Abstract: Delineating and classifying individual trees in remote sensing data is challenging. Many tree crown delineation methods have difficulty in closed-canopy forests and do not leverage multiple datasets. Methods to classify individual species are often accurate for common species, but perform poorly for less common species and when applied to new sites. We ran a […]

Congratulations to our labmate, Josh Peeples,  who was recently named an SEC Emerging Scholar!   The SEC Emerging Scholars program was designed to promote historically underrepresented groups to seek out academic positions in the SEC.  As a scholar, Josh is invited to attend a multi-day workshop where representatives from all fourteen SEC schools will host presentations […]

Congratulations to our labmates, Lucia Carrero and MaTais Caldwell!   Lucia and MaTais recently presented on their summer REU work — both did a great job!  

Dr. Jose F. Ruiz-Munoz of @Gator_Sense Lab will start a new position as an Assistant Professor at the National University of Colombia. He will join the computer programming and data analysis faculty team of the statistics program at La Paz campus. Congratulations, Jose! He is broadly interested in data analysis, signal processing, and machine learning applications. […]

Congratulations to our labmates and collaborators: V. R. Merenda, Jose Ruiz-Munoz, Alina Zare,  R. C. Chebel!  Their paper, “Predictive models to identify Holstein cows at risk of metritis and clinical cure and reproductive/productive failure following antimicrobial treatment”, was recently accepted to Preventive Veterinary Medicine.  In the paper, the authors investigated whether the use of behavioral […]

Abstract: Precision dairy farming, specifically the design of management strategies according to the animal’s needs, may soon become the norm since automated technologies that generate large amounts of data for each individual are becoming more affordable. Our objectives were to determine whether the use of behavioral changes could improve the accuracy of prediction of the […]

Abstract: We present a histogram layer for artificial neural networks (ANNs). An essential aspect of texture analysis is the extraction of features that describe the distribution of values in local spatial regions. The proposed histogram layer directly computes the spatial distribution of features for texture analysis and parameters for the layer are estimated during backpropagation. […]

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 excited to see what comes from her work! Great job, Xiaolei!

Congratulations to our labmates and collaborators: Ben Weinstein, Sarah Graves, Sergio Marconi, Aditya Singh, Alina Zare, Dylan Stewart, Stephanie Bohlman and Ethan P. White!  Their paper, “A benchmark dataset for individual tree crown delineation in co-registered airborne RGB, LiDAR and hyperspectral imagery from the National Ecological Observation Network”, was recently accepted to PLOS Computational Biology.  […]