Congratulations to our labmate Lysny Woodahl and her team GatorSynchro for placing 5th overall and 1st among Club teams at the Synchronized Swimming Collegiate Nationals in Columbus, OH! Lysny individually placed 1st in C figures and her duet placed 9th… Read More
Month: March 2017
Congratulations labmate Anand Seethepalli on new position
Congratulations to our former labmate, Anand Seethepalli on his new appointment as a Research Associate at the Samuel Roberts Noble Foundation! Anand will be working with Dr. Larry York on projects related to and extending his Masters thesis work on… Read More
Welcome new PhD student Joshua Peeples!
The Machine Learning and Sensing Lab is excited to welcome Joshua Peeples to our lab as a new Ph.D. student! Joshua has recently been awarded the Graduate School Preeminence Award (GSPA) to fund his studies at the University of Florida!… Read More
Binary Fuzzy Measures and Choquet Integration for Multi-Source Fusion
Abstract: Countless challenges in engineering require the intelligent combining (aka fusion) of data or information from multiple sources. The Choquet integral (ChI), a parametric aggregation function, is a well-known tool for multisource fusion, where source refers to sensors, humans and/or… Read More
Multiple-instance learning-based sonar image classification
Abstract: An approach to image labeling by seabed context based on multiple-instance learning via embedded instance selection (MILES) is presented. Sonar images are first segmented into superpixels with associated intensity and texture feature distributions. These superpixels are defined as the… Read More
Environmentally-Adaptive Target Recognition for SAS Imagery
Abstract: Characteristics of underwater targets displayed in synthetic aperture sonar (SAS) imagery vary depending on their environmental context. Discriminative features in sea grass may differ from the features that are discriminative in sand ripple, for example. Environmentally-adaptive target detection and… Read More
Hyperspectral Unmixing with Endmember Variability using Semi-supervised Partial Membership Latent Dirichlet Allocation
Abstract: A semi-supervised Partial Membership Latent Dirichlet Allocation approach is developed for hyperspectral unmixing and endmember estimation while accounting for spectral variability and spatial information. Partial Membership Latent Dirichlet Allocation is an effective approach for spectral unmixing while representing spectral… Read More
Genetic Programming Based Choquet Integral for Multi-Source Fusion
Abstract: While the Choquet integral (ChI) is a powerful parametric nonlinear aggregation function, it has limited scope and is not a universal function generator. Herein, we focus on a class of problems that are outside the scope of a single… Read More
Classification Label Map for MUUFL Gulfport Released!
We are excited to announce that we have released a classification label map for the MUUFL Gulfport co-registered hyperspectral and Lidar Campus 1 image . The MUUFL Gulfport data set was collected in November 2010 over the campus of the… Read More
Welcome new PhD student Connor McCurley!
The Machine Learning and Sensing Lab is excited to welcome Connor McCurley to the Lab as a new Ph.D. student! Connor has recently been awarded the Graduate School Preeminence Award (GSPA) to fund his studies at the University of Florida!… Read More