Mikhail Kanevski

发表

Multisensor Change Detection with Nonlinear Canonical Correlation

Gustavo Camps-Valls, Michele Volpi, Devis Tuia, 2013, IGARSS 2013.

Interactions between spatial complexity and distributed hydrological model response: towards the better identification and handling of structural error in model predictions.

Mikhail Kanevski, Vincent Humphrey, Stuart Lane, 2013 .

Wavelet Scale Variance Analysis of Wind Extremes in Mountainous Terrains

Mikhail Kanevski, Luciano Telesca, Fabian Guignard, 2019, Energies.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

Mikhail Kanevski, Loris Foresti, Sylvain Robert, 2013 .

A Special Issue on Data Science for Geosciences

Vasily Demyanov, Mikhail Kanevski, Erwan Gloaguen, 2019, Mathematical Geosciences.

Analysis and mapping of mountain permafrost data: a comparison between two machine learning algorithms

Mikhail Kanevski, Nicola Deluigi, Christophe Lambiel, 2015 .

Analysis of Pollution Patterns Using Unsupervised Machine Learning Algorithms

Mikhail Kanevski, V. Timonin, A. Pozdnoukhov, 2009 .

On Feature Selection Using Anisotropic General Regression Neural Network

Philippe Jacquet, Federico Amato, Mikhail Kanevski, 2020, ESANN.

Advanced Analysis of Temporal Data Using Fisher-Shannon Information: Theoretical Development and Application in Geosciences

Federico Amato, Mikhail Kanevski, Fabian Guignard, 2020, Frontiers in Earth Science.

A novel framework for spatio-temporal prediction of environmental data using deep learning

Mikhail Kanevski, Fabian Guignard, Sylvain Robert, 2020, Scientific Reports.

Flooded area cartography with kernel-based classifiers and Landsat TM imagery

George P. Petropoulos, Michele Volpi, Mikhail Kanevski, 2012 .

Spatio-Temporal Modeling of Wind Speed Using EOF and Machine Learning

Federico Amato, Mikhail Kanevski, Fabian Guignard, 2020 .

Unsupervised Feature Selection Based on the Morisita Index for Hyperspectral Images

Mikhail Kanevski, Jean Golay, 2017 .

Structured output SVM for remote sensing image classification

Gustavo Camps-Valls, Mikhail Kanevski, Jordi Muñoz-Marí, 2009 .

Model Variance for Extreme Learning Machine

Mikhail Kanevski, Fabian Guignard, Mohamed Laib, 2020, ESANN.

Indoor radon data monitoring networks : Topology, fractality and validity domains

Devis Tuia, Mikhail Kanevski, 2006 .

Improving permafrost distribution modelling using feature selection algorithms

Mikhail Kanevski, Nicola Deluigi, Christophe Lambiel, 2016 .

Mapping of Estimations and Prediction Intervals Using Extreme Learning Machines

Mikhail Kanevski, Michael Leuenberger, 2015 .

A new concept of wildland-urban interface based on city clustering algorithm

Mikhail Kanevski, Marj Tonini, Alexandre Champendal, 2012 .

Multivariate Mapping of Environmental Data Using Extreme Learning Machines

Mikhail Kanevski, Michael Leuenberger, 2014 .

Recent advances in environmental data mining

Mikhail Kanevski, Michael Leuenberger, 2016 .

Complex Environmental Data Modelling Using Adaptive General Regression Neural Networks

Mikhail Kanevski, 2015 .

Semi-supervised multiview embedding for hyperspectral data classification

Michele Volpi, Devis Tuia, Mikhail Kanevski, 2014, Neurocomputing.

A Novel Framework for Spatio-Temporal Prediction of Climate Data Using Deep Learning pdf

Federico Amato, Mikhail Kanevski, Fabian Guignard, 2020, ArXiv.

Active learning for monitoring network optimization

Devis Tuia, Mikhail Kanevski, Loris Foresti, 2012 .

Unsupervised Feature Selection Based on the Morisita Index

Mikhail Kanevski, Jean Golay, 2016 .

Advanced analysis of forest fire clustering

Mikhail Kanevski, Jean Golay, Mário G. Pereira, 2017 .

Extreme Learning Machines for spatial environmental data

Mikhail Kanevski, Michael Leuenberger, M. Kanevski, 2015, Comput. Geosci..

Spatio-temporal evolution of global surface temperature distributions

Federico Amato, Mikhail Kanevski, Vincent Humphrey, 2020, CI.

A new algorithm for redundancy minimisation in geo-environmental data

Mikhail Kanevski, Mohamed Laib, M. Kanevski, 2019, Comput. Geosci..

Uncertainty Quantification in Extreme Learning Machine: Analytical Developments, Variance Estimates and Confidence Intervals pdf

Federico Amato, Mikhail Kanevski, Fabian Guignard, 2020, Neurocomputing.

Multifractal portrayal of the distribution of the Swiss population

Mikhail Kanevski, Jean Golay, C. Vega-Orozco, 2012 .