Tag: hyperspectral

CLASSIFICATION WITH MULTI-IMPRECISE LABELS

Abstract: Links: Citation: S. Zou, “Classification with Multi-Imprecise Labels,” Ph.D. Thesis, Gainesville, FL, 2021. @phdthesis{Zou2021Thesis, author = {Sheng Zou}, title = {Classification with Multi-Imprecise Labels}, school = {Univ. of Florida}, year = {2021}, address = {Gainesville, FL}, month = {April},… Read More

SPECTRAL VARIABILITY IN HSI ACCEPTED TO GRSM!

Congratulations to our labmates and collaborators: Ricardo Augusto Borsoi, Tales Imbiriba, Jose Carlos Moreira Bermudez, Cedric Richard, Jocelyn Chanussot, Lucas Drumets, Jean-Yves Tourneret, Alina Zare and Christian Jutten!  Their publication, “Spectral Variability in Hyperspectral Data Unmixing: A Comprehensive Review” was… Read More

EVALUATION OF POSTHARVEST SENESCENCE IN BROCCOLI VIA HYPERSPECTRAL IMAGING

Abstract: Fresh fruits and vegetables are invaluable for human health, but their quality deteriorates before reaching consumers due to ongoing biochemical processes and compositional changes. The current lack of any objective indices for defining “freshness” of fruits or vegetables limits… Read More

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