Month: January 2019

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