Zobrazeno 1 - 10
of 279
pro vyhledávání: '"anomaly detection (AD)"'
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 14894-14907 (2024)
Anomaly detection (AD) aiming to locate targets distinct from the surrounding background spectra remains a challenging task in hyperspectral applications. The methods based on low-rank decomposition utilize the inherent low-rank characteristic of hyp
Externí odkaz:
https://doaj.org/article/0a1d48d82dc140ac966393aadcbda9ca
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 17, Pp 13966-13980 (2024)
In data acquisition and transmission, hyperspectral images are inevitably corrupted by additive noises, making it challenging to accurately observe and recognize the materials on the surface of the Earth. However, scholars have been addicted to devel
Externí odkaz:
https://doaj.org/article/239dc3e2eef74046bfa588ed17a411b5
Publikováno v:
Defence Technology, Vol 26, Iss , Pp 231-241 (2023)
The anomaly detection of electromagnetic environment situation (EMES) has essential reference value for electromagnetic equipment behavior cognition and battlefield threat assessment. In this paper, we proposed a deep learning-based method for detect
Externí odkaz:
https://doaj.org/article/48f17b6021c94619ab3c26c0b2ddfe73
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 16, Pp 1985-2008 (2023)
As one of the most important research and application directions in hyperspectral remote sensing, anomaly detection (AD) aims to locate objects of interest within a specific scene by exploiting spectral feature differences between different types of
Externí odkaz:
https://doaj.org/article/ad0194cc49154ac0a93803449916d3c4
Publikováno v:
Remote Sensing, Vol 15, Iss 18, p 4449 (2023)
The airborne hyperspectral remote sensing systems (AHRSSs) acquire images with high spectral resolution, high spatial resolution, and high temporal dimension. While the AHRSS captures more detailed information from the terrain objects, the computatio
Externí odkaz:
https://doaj.org/article/33021569b2304a749283b1174b7b641e
Publikováno v:
IEEE Open Journal of Instrumentation and Measurement, Vol 1, Pp 1-11 (2022)
Deep learning neural network serves as a powerful tool for visual anomaly detection (AD) and fault diagnosis, attributed to its strong abstractive interpretation ability in the representation domain. The deep features from neural networks that are pr
Externí odkaz:
https://doaj.org/article/bc2551fca1f24561bb94685beed4cf37
Akademický článek
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Akademický článek
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Visual Attention and Background Subtraction With Adaptive Weight for Hyperspectral Anomaly Detection
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 2270-2283 (2021)
Anomaly detection (AD) in hyperspectral target detection is of particular interest because no prior knowledge of ground object spectra is required. However, it is difficult to utilize the salient features of hyperspectral image (HSI) and mitigate the
Externí odkaz:
https://doaj.org/article/8e5b98cfc6f74ae688bb5301b7adfe98
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 14, Pp 4915-4932 (2021)
Orthogonal subspace projection (OSP) is a versatile hyperspectral imaging technique which has shown great potential in dimensionality reduction, target detection, spectral unmixing, etc. However, due to its inherent requirement of prior target knowle
Externí odkaz:
https://doaj.org/article/aeede8949c9148c68e4c23640f20983c