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Tensor-based anomaly detection: An interdisciplinary survey

Hadi Fanaee-T, João Gama
2016 Knowledge-Based Systems  
However, if data includes tensor (multiway) structure (e.g. space-time-measurements), some meaningful anomalies may remain invisible with these methods.  ...  This survey aims to highlight the potential of tensor-based techniques as a novel approach for detection and identification of abnormalities and failures.  ...  Remote sensing Nowadays, with the aid of hyperspectral imaging technology we are able to capture spectral images with a different range of spectra.  ... 
doi:10.1016/j.knosys.2016.01.027 fatcat:lejxxae63jcutfx2ncahownt7e

Advances in Hyperspectral Image and Signal Processing: A Comprehensive Overview of the State of the Art

Pedram Ghamisi, Naoto Yokoya, Jun Li, Wenzhi Liao, Sicong Liu, Javier Plaza, Behnood Rasti, Antonio Plaza
2017 IEEE Geoscience and Remote Sensing Magazine  
reduction, resolution enhancement, hyperspectral image denoising and restoration, change detection, and fast computing.  ...  Hence, rigorous and innovative methodologies are required for hyperspectral image and signal processing and have become a center of attention for researchers worldwide.  ...  In addition, the authors would like to thank the National Center for Airborne Laser Mapping (NCALM) at the University of Houston for providing the CASI Houston data set, and the IEEE GRSS Image Analysis  ... 
doi:10.1109/mgrs.2017.2762087 fatcat:6ezzye7yyvacbouduqv2f2c7gi

Development and Application of Chemometric Methods for Modelling Metabolic Spectral Profiles

Judith Marlou Fonville, Elaine Holmes, Jeremy Nicholson, Analytical Chemistry Trust Fund Of The Royal Society Of Chemistry
, especially in terms of interpretation and visualisation using colour-coding of images.  ...  Finally, the vast amount of data generated with mass spectrometry imaging is investigated in terms of data processing, and the benefits of applying multivariate techniques to these data are illustrated  ...  an orthogonal decomposition.  ... 
doi:10.25560/6952 fatcat:f5xai53kgzfgnoep7ve6ibxxiu