Torque is one of the mighty core parameters of rotating machinery, and it has profound
implications for the success of many engineering and industrial manufacturing activities. To …

Sparse representation (SR)-based approaches and collaborative representation (CR)-
based methods are proved to be effective to detect the anomalies in a hyperspectral image …

Low rank and sparse representation (LRSR) with dual-dictionaries-based methods for
detecting anomalies in hyperspectral images (HSIs) are proven to be effective. However, the …

Anomaly detection (AD) has attracted remarkable attention in hyperspectral image (HSI)
processing fields, and most existing deep learning (DL)-based algorithms indicate dramatic …

Hyperspectral anomaly detection is aimed at detecting targets with significant spectral
differences from their surroundings. Recently, deep generative models have been applied to …

The existing deep-learning-based hyperspectral anomaly detection methods detect
anomalies by reconstructing a clean background. However, these methods model the …

With hyperspectral remote sensors (imaging spectrometers) imaging a scene, the specificity
of the target of interest is manifested in the significant differences between it and the …

随着航空航天技术与遥感技术的不断发展, 遥感影像在诸多领域的应用不断拓展,
其中高光谱分辨率遥感影像具有“图谱合一” 的特点, 即该数据既包含了具有强大区分性的地物 …

Collaborative representation-based (CR) methods have received widespread attention in
hyperspectral anomaly detection, but the results are greatly affected by the quality of the …

Through the years, graph theory has gradually been applied in hyperspectral image (HSI)
processing. The graph theory method does not need to consider the structural …