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PIECEWISE ANOMALY DETECTION USING MINIMAL LEARNING MACHINE FOR HYPERSPECTRAL IMAGES

2021

Abstract. Hyperspectral imaging, with its applications, offers promising tools for remote sensing and Earth observation. Recent development has increased the quality of the sensors. At the same time, the prices of the sensors are lowering. Anomaly detection is one of the popular remote sensing applications, which benefits from real-time solutions. A real-time solution has its limitations, for example, due to a large amount of hyperspectral data, platform’s (drones or a cube satellite) constraints on payload and processing capability. Other examples are the limitations of available energy and the complexity of the machine learning models. When anomalies are detected in real-time from the hyp…

TechnologyMinimal Learning Machinehyperspectral imagingComputer scienceRemote sensing applicationConstant false alarm rateRobustness (computer science)Applied optics. Photonicshyperspektrikuvantaminenbusiness.industryTspektrikuvausPayload (computing)Hyperspectral imagingPattern recognitionEngineering (General). Civil engineering (General)anomaly detectionTA1501-1820piecewise approachmachine learningkoneoppiminenPiecewiseAnomaly detectionNoise (video)Artificial intelligenceTA1-2040businessreal-time computationISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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