Tag: hyperspectral

A BENCHMARK DATASET FOR INDIVIDUAL TREE CROWN DELINEATION IN CO-REGISTERED AIRBORNE RGB, LIDAR AND HYPERSPECTRAL IMAGERY FROM THE NATIONAL ECOLOGICAL OBSERVATION NETWORK

Abstract: Broad scale remote sensing promises to build forest inventories at unprecedented scales. A crucial step in this process is designing individual tree segmentation algorithms to associate pixels into delineated tree crowns. While dozens of tree delineation algorithms have been… Read More

Multi-Target Multiple Instance Learning for Hyperspectral Target Detection

Abstract: In remote sensing, it is often challenging to acquire or collect a large dataset that is accurately labeled. This difficulty is usually due to several issues, including but not limited to the study site’s spatial area and accessibility, errors… Read More

Spectral Variability in Hyperspectral Data Unmixing: A Comprehensive Review

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… Read More

Master’s Defenses!

Congratulations to our labmates, Hudanyun Sheng and Princess Lyons, for successful Master’s defenses!   Hudanyun conducted work on “Switchgrass Genotype Classification using Hyperspectral Imagery”, while Princess investigated  “Anomaly and Target Detection in Synthetic Aperture Sonar”. Great job, you two!

Peanut Maturity Classification using Hyperspectral Imagery

Abstract: Seed maturity in peanut ( Arachis hypogaea L.) determines economic return to a producer because of its impact on seed weight, and critically influences seed vigor and other quality characteristics. During seed development, the inner mesocarp layer of the… Read More

Du Accepted to The 2019 IEEE Symposium Series on Computational Intelligence (IEEE SSCI 2019)

Congratulations to Gatorsense alumna, Xiaoxiao Du!  Her paper, titled “Multiple Instance Choquet Integral with Binary Fuzzy Measures for Remote Sensing Classifier Fusion with Imprecise Labels”, was recently accepted for publication with The 2019 IEEE Symposium Series on Computational Intelligence (IEEE… Read More