Tag: endmember

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

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

Multiple Instance Choquet Integral with Binary Fuzzy Measures for Remote Sensing Classifier Fusion with Imprecise Labels

Abstract: Classifier fusion methods integrate complementary information from multiple classifiers or detectors and can aid remote sensing applications such as target detection and hyperspectral image analysis. The Choquet integral (CI), parameterized by fuzzy measures (FMs), has been widely used in… Read More

Plant species’ spectral emissivity and temperature using the hyperspectral thermal emission spectrometer (HyTES) sensor

Abstract: The thermal domain (TIR; 2.5–15 μm) delivers unique measurements of plant characteristics that are not possible in other parts of the electromagnetic spectrum. However, these TIR measurements have largely been restricted to laboratory leaf level or coarse spatial resolutions… Read More