most citedHyperspectral Anomaly Detection Using Einstein Fuzzy Computing and Quantum Neural Network

1 citations · 2 across the 3 of their papers we have counts for

collaborators

5 papers

eess.IV2026

Anti-Hyperspectral Anomaly Detection: A First Study on Stealthy Lipschitz-Forcing Perturbations Against Unknown Detectors

Chia-Hsiang Lin, Si-Sheng Young, Jon Atli Benediktsson

Hyperspectral imagery represents the best contemporary technology to remotely detect anomalous objects. Nevertheless, hyperspectral anomaly detection (HAD) technique makes ground f…

eess.IV20261 cited

Hyperspectral Anomaly Detection Using Einstein Fuzzy Computing and Quantum Neural Network

Chia-Hsiang Lin, Si-Sheng Young, Reza Langari

In the remote sensing (RS) field, hyperspectral imagery provides rich spectral information and facilitates numerous critical applications, such as material identification. Among th…

eess.IV20261 cited

Underdetermined Blind Source Separation via Weighted Simplex Shrinkage Regularization and Quantum Deep Image Prior

Chia-Hsiang Lin, Si-Sheng Young

As most optical satellites remotely acquire multispectral images (MSIs) with limited spatial resolution, multispectral unmixing (MU) becomes a critical signal processing technology…

eess.IV2026

Spectral Super-Resolution via Adversarial Unfolding and Data-Driven Spectrum Regularization: From Multispectral Satellite Data to NASA Hyperspectral Image

Si-Sheng Young, Chia-Hsiang Lin

The European Space Agency's Sentinel-2 satellite provides global multispectral coverage for remote sensing (RS) applications. However, limited spectral resolution (12 bands) and no…

eess.IV2025

HyperKING: Quantum-Classical Generative Adversarial Networks for Hyperspectral Image Restoration

Chia-Hsiang Lin, Si-Sheng Young

Quantum machine intelligence starts showing its impact on satellite remote sensing (SRS). Also, recent literature exhibits that quantum generative intelligences encompass superior…