Search Results for author: Sheng Zou

Found 5 papers, 0 papers with code

Cross-Layered Distributed Data-driven Framework For Enhanced Smart Grid Cyber-Physical Security

no code implementations10 Nov 2021 Allen Starke, Keerthiraj Nagaraj, Cody Ruben, Nader Aljohani, Sheng Zou, Arturo Bretas, Janise McNair, Alina Zare

Smart Grid (SG) research and development has drawn much attention from academia, industry and government due to the great impact it will have on society, economics and the environment.

Anomaly Detection

Peanut Maturity Classification using Hyperspectral Imagery

no code implementations20 Oct 2019 Sheng Zou, Yu-Chien Tseng, Alina Zare, Diane Rowland, Barry Tillman, Seung-Chul Yoon

The maturity assessment process involves the removal of the exocarp of the hull and visually categorizing the mesocarp color into varying color classes from immature (white, yellow, orange) to mature (brown, and black).

Classification General Classification

Hyperspectral Unmixing with Endmember Variability using Semi-supervised Partial Membership Latent Dirichlet Allocation

no code implementations17 Mar 2017 Sheng Zou, Hao Sun, Alina Zare

A semi-supervised Partial Membership Latent Dirichlet Allocation approach is developed for hyperspectral unmixing and endmember estimation while accounting for spectral variability and spatial information.

Hyperspectral Unmixing

Hyperspectral Unmixing with Endmember Variability using Partial Membership Latent Dirichlet Allocation

no code implementations12 Sep 2016 Sheng Zou, Alina Zare

The application of Partial Membership Latent Dirichlet Allocation(PM-LDA) for hyperspectral endmember estimation and spectral unmixing is presented.

Hyperspectral image analysis Hyperspectral Unmixing

Instance Influence Estimation for Hyperspectral Target Signature Characterization using Extended Functions of Multiple Instances

no code implementations21 Mar 2016 Sheng Zou, Alina Zare

From these imprecise labels, eFUMI has been shown to be effective at estimating target signatures in hyperspectral subpixel target detection problems.

Multiple Instance Learning

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