Machine Learning Techniques Applied to Geoscience Information System and Remote Sensing |
Autore | Lee Saro |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
Descrizione fisica | 1 electronic resource (438 p.) |
Soggetto non controllato |
artificial neural network
model switching sensitivity analysis neural networks logit boost Qaidam Basin land subsidence land use/land cover (LULC) naïve Bayes multilayer perceptron convolutional neural networks single-class data descriptors logistic regression feature selection mapping particulate matter 10 (PM10) Bayes net gray-level co-occurrence matrix multi-scale Logistic Model Trees classification Panax notoginseng large scene coarse particle grayscale aerial image Gaofen-2 environmental variables variable selection spatial predictive models weights of evidence landslide prediction random forest boosted regression tree convolutional network Vietnam model validation colorization data mining techniques spatial predictions SCAI unmanned aerial vehicle high-resolution texture spatial sparse recovery landslide susceptibility map machine learning reproducible research constrained spatial smoothing support vector machine random forest regression model assessment information gain ALS point cloud bagging ensemble one-class classifiers leaf area index (LAI) landslide susceptibility landsat image ionospheric delay constraints spatial spline regression remote sensing image segmentation panchromatic Sentinel-2 remote sensing optical remote sensing materia medica resource GIS precise weighting change detection TRMM traffic CO crop training sample size convergence time object detection gully erosion deep learning classification-based learning transfer learning landslide traffic CO prediction hybrid model winter wheat spatial distribution logistic alternating direction method of multipliers hybrid structure convolutional neural networks geoherb predictive accuracy real-time precise point positioning spectral bands |
ISBN | 3-03921-216-8 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910367564103321 |
Lee Saro
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MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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New Developments in Statistical Information Theory Based on Entropy and Divergence Measures |
Autore | Pardo Leandro |
Pubbl/distr/stampa | MDPI - Multidisciplinary Digital Publishing Institute, 2019 |
Descrizione fisica | 1 electronic resource (344 p.) |
Soggetto non controllato |
mixture index of fit
Kullback-Leibler distance relative error estimation minimum divergence inference Neyman Pearson test influence function consistency thematic quality assessment asymptotic normality Hellinger distance nonparametric test Berstein von Mises theorem maximum composite likelihood estimator 2-alternating capacities efficiency corrupted data statistical distance robustness log-linear models representation formula goodness-of-fit general linear model Wald-type test statistics Hölder divergence divergence logarithmic super divergence information geometry sparse robust estimation relative entropy minimum disparity methods MM algorithm local-polynomial regression association models total variation Bayesian nonparametric ordinal classification variables Wald test statistic Wald-type test composite hypotheses compressed data hypothesis testing Bayesian semi-parametric single index model indoor localization composite minimum density power divergence estimator quasi-likelihood Chernoff Stein lemma composite likelihood asymptotic property Bregman divergence robust testing misspecified hypothesis and alternative least-favorable hypotheses location-scale family correlation models minimum penalized ?-divergence estimator non-quadratic distance robust semiparametric model divergence based testing measurement errors bootstrap distribution estimator generalized renyi entropy minimum divergence methods generalized linear model ?-divergence Bregman information iterated limits centroid model assessment divergence measure model check two-sample test Wald statistic |
ISBN | 3-03897-937-6 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Record Nr. | UNINA-9910346856403321 |
Pardo Leandro
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MDPI - Multidisciplinary Digital Publishing Institute, 2019 | ||
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Lo trovi qui: Univ. Federico II | ||
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