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Recognizing Submerged Materials with Fluorescence Lidar without Knowledge of Environmental Conditions.

, , и . IGARSS, стр. 82-85. IEEE, (2019)

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Julien Corsini

Lorenzo Corsini

Giovanni Natale

Giovanni Bacigalupo

Giovanni Lamura

 

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Underwater Material Discriminability with Fluorescence Lidar in Unknown Environmental Conditions., и . IGARSS, стр. 4599-4602. IEEE, (2018)A New Band Selection Strategy for Target Detection in Hyperspectral Images., , , и . KES (3), том 5179 из Lecture Notes in Computer Science, стр. 424-431. Springer, (2008)Target detection experiments with a non-parametric detector on a new hyperspectral data set., , и . IGARSS, стр. 1328-1331. IEEE, (2017)Effects of signal contamination in RX detection of local hyperspectral anomalies., , и . IGARSS, стр. 4845-4848. IEEE, (2012)Multi-temporal approach to atmospheric effects compensation in hyperspectral image classification., , , и . IGARSS, стр. 1670-1673. IEEE, (2015)Signal-to-noise ratio and autocorrelation function of the image intensity in coherent systems. Sub-Rayleigh and super-Rayleigh conditions., , и . IEEE Trans. Image Process., 5 (1): 132-141 (1996)PRISMA Spatial Resolution Enhancement by Fusion With Sentinel-2 Data., , и . IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens., (2022)Fully Unsupervised Learning of Gaussian Mixtures for Anomaly Detection in Hyperspectral Imagery., , , и . ISDA, стр. 596-601. IEEE Computer Society, (2009)Validation of forward modeling target detection approach on a new hyperspectral data set featuring an urban scenario and variable illumination conditions., , , , , и . IGARSS, стр. 5075-5078. IEEE, (2015)Sentinel-2 Image Generation via Stylegan3 Model., , и . WHISPERS, стр. 1-5. IEEE, (2023)