Author: cuiyiming@ufl.edu

Root Identification in Minirhizotron Imagery with Multiple Instance Learning

Abstract: In this paper, multiple instance learning (MIL) algorithms to automatically perform root detection and segmentation in minirhizotron imagery using only image-level labels are proposed. Root and soil characteristics vary from location to location, thus, supervised machine learning approaches that… Read More

Complex Scene Classification of PoLSAR Imagery Based on a Self-Paced Learning Approach

Abstract: Existing polarimetric synthetic aperture radar (PolSAR) image classification methods cannot achieve satisfactory performance on complex scenes characterized by several types of land cover with significant levels of noise or similar scattering properties across land cover types. Hence, we propose… Read More

Welcome new Post-doctoral Scientist Susan Meerdink!

The Machine Learning and Sensing Lab is excited to welcome our newest lab member Susan Meerdink! Susan got her M.S. and Ph.D. degrees from University of California Santa Barbara. She studies the ability to map plant species across seasons in… Read More

Welcome to our new undergraduate students!

The Machine Learning and Sensing Lab is excited to welcome our newest lab members Alyssa Bowles, Caleb Robey, Layiwola Lawrence Ibukun, Jake Samuelson, Ross Spencer, Val Christian and Yutai Zhou! They will be working on : Alyssa, Ross, and Val… Read More

Bocinsky and McCurley present in DC

Our labmates James Bocinsky and Connor McCurley recently presented their work on buried explosive object detection at a project meeting in Washington D.C. They did a great job presenting their work – and had some time to see the sights!