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ORCIDMikhail F. Kanevski
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2020 – today
- 2021
[j30]Fabian Guignard, Federico Amato, Mikhail F. Kanevski:
Uncertainty quantification in extreme learning machine: Analytical developments, variance estimates and confidence intervals. Neurocomputing 456: 436-449 (2021)- [i9]Devis Tuia, Michele Volpi, Loris Copa, Mikhail F. Kanevski, Jordi Muñoz-Marí:
A survey of active learning algorithms for supervised remote sensing image classification. CoRR abs/2104.07784 (2021) - [i8]Federico Amato, Fabian Guignard, Alina Walch, Nahid Mohajeri, Jean-Louis Scartezzini, Mikhail F. Kanevski:
Spatio-temporal estimation of wind speed and wind power using machine learning: predictions, uncertainty and technical potential. CoRR abs/2108.00859 (2021) - 2020
- [c40]Federico Amato, Fabian Guignard, Vincent Humphrey, Mikhail F. Kanevski:
Spatio-temporal evolution of global surface temperature distributions. CI 2020: 37-43 - [c39]Federico Amato, Fabian Guignard, Philippe Jacquet, Mikhail F. Kanevski:
On Feature Selection Using Anisotropic General Regression Neural Network. ESANN 2020: 411-416 - [c38]Fabian Guignard, Mohamed Laib, Mikhail F. Kanevski:
Model Variance for Extreme Learning Machine. ESANN 2020: 703-708 - [c37]Mikhail F. Kanevski
, Mohamed Laib:
Unsupervised Learning of High Dimensional Environmental Data Using Local Fractality Concept. ICPR Workshops (6) 2020: 130-138 - [i7]Federico Amato, Fabian Guignard, Vincent Humphrey, Mikhail F. Kanevski:
Spatio-temporal evolution of global surface temperature distributions. CoRR abs/2006.12386 (2020) - [i6]Federico Amato, Fabian Guignard, Sylvain Robert, Mikhail F. Kanevski:
A Novel Framework for Spatio-Temporal Prediction of Climate Data Using Deep Learning. CoRR abs/2007.11836 (2020) - [i5]Federico Amato, Fabian Guignard, Philippe Jacquet, Mikhail F. Kanevski:
On Feature Selection Using Anisotropic General Regression Neural Network. CoRR abs/2010.05744 (2020) - [i4]Fabian Guignard, Federico Amato, Mikhail F. Kanevski:
Uncertainty Quantification in Extreme Learning Machine: Analytical Developments, Variance Estimates and Confidence Intervals. CoRR abs/2011.01704 (2020)
2010 – 2019
- 2019
- [j29]Fabian Guignard, Dasaraden Mauree, Michele Lovallo, Mikhail F. Kanevski, Luciano Telesca:
Fisher-Shannon Complexity Analysis of High-Frequency Urban Wind Speed Time Series. Entropy 21(1): 47 (2019) - [j28]Mohamed Laib, Mikhail F. Kanevski:
A new algorithm for redundancy minimisation in geo-environmental data. Comput. Geosci. 133 (2019) - 2018
- [j27]Michael Leuenberger, Joana Parente, Marj Tonini, Mário G. Pereira, Mikhail F. Kanevski:
Wildfire susceptibility mapping: Deterministic vs. stochastic approaches. Environ. Model. Softw. 101: 194-203 (2018) - [j26]Federico Amato, Marj Tonini, Beniamino Murgante, Mikhail F. Kanevski:
Fuzzy definition of Rural Urban Interface: An application based on land use change scenarios in Portugal. Environ. Model. Softw. 104: 171-187 (2018) - [c36]Mohamed Laib, Mikhail F. Kanevski:
A novel filter algorithm for unsupervised feature selection based on a space filling measure. ESANN 2018 - 2017
- [j25]Jean Golay, Mikhail F. Kanevski:
Unsupervised feature selection based on the Morisita estimator of intrinsic dimension. Knowl. Based Syst. 135: 125-134 (2017) - [j24]Jean Golay, Michael Leuenberger, Mikhail F. Kanevski:
Feature selection for regression problems based on the Morisita estimator of intrinsic dimension. Pattern Recognit. 70: 126-138 (2017) - [i3]Mohamed Laib, Mikhail F. Kanevski:
Unsupervised Feature Selection Based on Space Filling Concept. CoRR abs/1706.08894 (2017) - 2016
- [j23]Fabio Aiolli, Kerstin Bunte, Romain Hérault, Mikhail F. Kanevski:
Special issue: Advances in artificial neural networks, machine learning and computational intelligenceSelected papers from the 23rd European Symposium on Artificial Neural Networks (ESANN 2015). Neurocomputing 192: 1-2 (2016) - [i2]Jean Golay, Michael Leuenberger, Mikhail F. Kanevski:
Feature Selection for Regression Problems Based on the Morisita Estimator of Intrinsic Dimension: Concept and Case Studies. CoRR abs/1602.00216 (2016) - [i1]Jean Golay, Mikhail F. Kanevski:
Unsupervised Feature Selection Based on the Morisita Estimator of Intrinsic Dimension. CoRR abs/1608.05581 (2016) - 2015
- [j22]Mikhail F. Kanevski, Vasiliy V. Demyanov:
Statistical learning in geoscience modelling: Novel algorithms and challenging case studies. Comput. Geosci. 85: 1-2 (2015) - [j21]Michael Leuenberger, Mikhail F. Kanevski:
Extreme Learning Machines for spatial environmental data. Comput. Geosci. 85: 64-73 (2015) - [j20]Jean Golay, Mikhail F. Kanevski:
A new estimator of intrinsic dimension based on the multipoint Morisita index. Pattern Recognit. 48(12): 4070-4081 (2015) - [j19]Giona Matasci, Michele Volpi, Mikhail F. Kanevski, Lorenzo Bruzzone, Devis Tuia:
Semisupervised Transfer Component Analysis for Domain Adaptation in Remote Sensing Image Classification. IEEE Trans. Geosci. Remote. Sens. 53(7): 3550-3564 (2015) - [c35]Jean Golay, Michael Leuenberger, Mikhail F. Kanevski:
Morisita-based feature selection for regression problems. ESANN 2015 - 2014
- [j18]Michele Volpi, Giona Matasci, Mikhail F. Kanevski, Devis Tuia:
Semi-supervised multiview embedding for hyperspectral data classification. Neurocomputing 145: 427-437 (2014) - [c34]Michael Leuenberger, Mikhail F. Kanevski:
Feature selection in environmental data mining combining Simulated Annealing and Extreme Learning Machine. ESANN 2014 - [c33]Antonino Marvuglia, Mikhail F. Kanevski, Michael Leuenberger, Enrico Benetto:
Variables Selection for Ecotoxicity and Human Toxicity Characterization Using Gamma Test. ICCSA (3) 2014: 640-652 - [c32]Alexandre Champendal, Mikhail F. Kanevski, Pierre-Emmanuel Huguenot:
Air Pollution Mapping Using Nonlinear Land Use Regression Models. ICCSA (3) 2014: 682-690 - [c31]Giona Matasci, Frank de Morsier, Mikhail F. Kanevski, Devis Tuia:
Domain adaptation in remote sensing through cross-image synthesis with dictionaries. IGARSS 2014: 3714-3717 - 2013
- [j17]Michele Volpi, Devis Tuia, Francesca Bovolo, Mikhail F. Kanevski, Lorenzo Bruzzone:
Supervised change detection in VHR images using contextual information and support vector machines. Int. J. Appl. Earth Obs. Geoinformation 20: 77-85 (2013) - [j16]Michele Volpi, George P. Petropoulos, Mikhail F. Kanevski:
Flooding extent cartography with Landsat TM imagery and regularized kernel Fisher's discriminant analysis. Comput. Geosci. 57: 24-31 (2013) - [j15]Marc Revilloud, Jean-Christophe Loubier, Marut Doctor, Mikhail F. Kanevski, Vadim Timonin, Michael Ignaz Schumacher:
Predicting snow height in ski resorts using an agent-based simulation. Multiagent Grid Syst. 9(4): 279-299 (2013) - [c30]Michele Volpi, Giona Matasci, Mikhail F. Kanevski, Devis Tuia:
Multi-view feature extraction for hyperspectral image classification. ESANN 2013 - [c29]Giona Matasci, Lorenzo Bruzzone, Michele Volpi, Devis Tuia, Mikhail F. Kanevski:
Investigating Feature Extraction for Domain Adaptation in Remote Sensing Image Classification. ICPRAM 2013: 419-424 - [c28]Michele Volpi, Frank de Morsier, Gustavo Camps-Valls, Mikhail F. Kanevski, Devis Tuia:
Multi-sensor change detection based on nonlinear canonical correlations. IGARSS 2013: 1944-1947 - [c27]Giona Matasci, Nathan Longbotham, Fabio Pacifici, Mikhail F. Kanevski, Devis Tuia:
Statistical assessment of dataset shift and model portability in multi-angle in-track image acquisitions. IGARSS 2013: 4134-4137 - 2012
- [j14]Michele Volpi, Devis Tuia, Gustavo Camps-Valls, Mikhail F. Kanevski:
Unsupervised Change Detection With Kernels. IEEE Geosci. Remote. Sens. Lett. 9(6): 1026-1030 (2012) - [j13]Giona Matasci, Devis Tuia, Mikhail F. Kanevski:
SVM-Based Boosting of Active Learning Strategies for Efficient Domain Adaptation. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 5(5): 1335-1343 (2012) - [j12]Loris Foresti, Mikhail F. Kanevski, Alexei Pozdnoukhov:
Kernel-Based Mapping of Orographic Rainfall Enhancement in the Swiss Alps as Detected by Weather Radar. IEEE Trans. Geosci. Remote. Sens. 50(8): 2954-2967 (2012) - [j11]Michele Volpi, Devis Tuia, Mikhail F. Kanevski:
Memory-Based Cluster Sampling for Remote Sensing Image Classification. IEEE Trans. Geosci. Remote. Sens. 50(8): 3096-3106 (2012) - [c26]Michele Volpi, Giona Matasci, Devis Tuia, Mikhail F. Kanevski:
Enhanced change detection using nonlinear feature extraction. IGARSS 2012: 6757-6760 - 2011
- [j10]Devis Tuia, Michele Volpi, Loris Copa, Mikhail F. Kanevski, Jordi Muñoz-Marí:
A Survey of Active Learning Algorithms for Supervised Remote Sensing Image Classification. IEEE J. Sel. Top. Signal Process. 5(3): 606-617 (2011) - [j9]Devis Tuia, Jordi Muñoz-Marí, Mikhail F. Kanevski, Gustavo Camps-Valls:
Structured Output SVM for Remote Sensing Image Classification. J. Signal Process. Syst. 65(3): 301-310 (2011) - [c25]Michele Volpi, Devis Tuia, Gustavo Camps-Valls, Mikhail F. Kanevski:
Unsupervised change detection in the feature space using kernels. IGARSS 2011: 106-109 - [c24]Giona Matasci, Devis Tuia, Mikhail F. Kanevski:
Domain separation for efficient adaptive active learning. IGARSS 2011: 3716-3719 - [c23]Marc Revilloud, Jean-Christophe Loubier, Marut Doctor, Mikhail F. Kanevski, Vadim Timonin, M. Schumacher:
Artificial Snow Optimization in Winter Sport Destinations Using a Multi-agent Simulation. PAAMS 2011: 201-210 - 2010
- [j8]Devis Tuia, Frédéric Ratle, Fabio Pacifici, Mikhail F. Kanevski, William J. Emery:
Correction to "Active Learning Methods for Remote Sensing Image Classification" [Jul 09 2218-2232]. IEEE Trans. Geosci. Remote. Sens. 48(6): 2767 (2010) - [j7]Devis Tuia, Gustavo Camps-Valls, Giona Matasci, Mikhail F. Kanevski:
Learning Relevant Image Features With Multiple-Kernel Classification. IEEE Trans. Geosci. Remote. Sens. 48(10): 3780-3791 (2010) - [c22]Loris Foresti, Devis Tuia, Vadim Timonin, Mikhail F. Kanevski:
Time series input selection using multiple kernel learning. ESANN 2010 - [c21]Mikhail F. Kanevski, Vadim Timonin:
Machine learning analysis and modeling of interest rate curves. ESANN 2010 - [c20]Michele Volpi, Devis Tuia, Mikhail F. Kanevski:
Advanced active sampling for remote sensing image classification. IGARSS 2010: 1414-1417 - [c19]Devis Tuia, Mikhail F. Kanevski, Jordi Muñoz-Marí, Gustavo Camps-Valls:
Cluster-based active learning for compact image classification. IGARSS 2010: 2824-2827
2000 – 2009
- 2009
- [j6]Devis Tuia, Christian Kaiser, Antonio Da Cunha, Mikhail F. Kanevski:
Clustering and Hot Spot Detection in Socio-economic Spatio-temporal Data. Trans. Comput. Sci. 6: 234-250 (2009) - [j5]Devis Tuia, Frédéric Ratle, Fabio Pacifici, Mikhail F. Kanevski, William J. Emery:
Active Learning Methods for Remote Sensing Image Classification. IEEE Trans. Geosci. Remote. Sens. 47(7-2): 2218-2232 (2009) - [j4]Devis Tuia, Fabio Pacifici, Mikhail F. Kanevski, William J. Emery:
Classification of Very High Spatial Resolution Imagery Using Mathematical Morphology and Support Vector Machines. IEEE Trans. Geosci. Remote. Sens. 47(11): 3866-3879 (2009) - [c18]S. B. Bai, J. Wang, Alexei Pozdnoukhov, Mikhail F. Kanevski:
Validation of Logistic Regression Models for Landslide Susceptibility Maps. CSIE (2) 2009: 355-358 - [c17]Loris Foresti, Devis Tuia, Alexei Pozdnoukhov, Mikhail F. Kanevski:
Multiple Kernel Learning of Environmental Data. Case Study: Analysis and Mapping of Wind Fields. ICANN (2) 2009: 933-943 - [c16]Devis Tuia, Giona Matasci, Gustavo Camps-Valls, Mikhail F. Kanevski:
Learning the Relevant Image Features with Multiple Kernels. IGARSS (2) 2009: 65-68 - 2008
- [j3]Dominique Fasbender, Devis Tuia, Patrick Bogaert, Mikhail F. Kanevski:
Support-Based Implementation of Bayesian Data Fusion for Spatial Enhancement: Applications to ASTER Thermal Images. IEEE Geosci. Remote. Sens. Lett. 5(4): 598-602 (2008) - [c15]Alexei Pozdnoukhov, Mikhail F. Kanevski:
GeoKernels: modeling of spatial data on geomanifolds. ESANN 2008: 277-282 - [c14]S. B. Bai, J. Wang, F. Y. Zhang, Alexei Pozdnoukhov, Mikhail F. Kanevski:
Prediction of Landslide Susceptibility Using logistic Regression: A Case Study in Bailongjiang River Basin, China. FSKD (4) 2008: 647-651 - [c13]Devis Tuia, Christian Kaiser, Antonio Da Cunha, Mikhail F. Kanevski:
Socio-economic Data Analysis with Scan Statistics and Self-organizing Maps. ICCSA (1) 2008: 52-64 - [c12]Mikhail F. Kanevski, Vadim Timonin, Alexei Pozdnoukhov:
Automatic Decision-Oriented Mapping of Pollution Data. ICCSA (1) 2008: 678-691 - [c11]Devis Tuia, Frédéric Ratle, Fabio Pacifici, Alexei Pozdnoukhov, Mikhail F. Kanevski, Fabio Del Frate, Domenico Solimini, William J. Emery:
Active Learning of Very-High Resolution Optical Imagery with SVM: Entropy vs Margin Sampling. IGARSS (4) 2008: 73-76 - 2007
- [j2]Mikhail F. Kanevski, Alexei Pozdnoukhov, Vadim Timonin, Michel Maignan:
Mapping of environmental data using kernel-based methods. Rev. Int. Géomatique 17(3-4): 309-331 (2007) - [c10]Frédéric Ratle, Mikhail F. Kanevski, Anne-Laure Terrettaz-Zufferey, Pierre Esseiva, Olivier Ribaux:
A Comparison of One-Class Classifiers for Novelty Detection in Forensic Case Data. IDEAL 2007: 67-76 - 2006
- [c9]Frédéric Ratle, Anne-Laure Terrettaz, Mikhail F. Kanevski, Pierre Esseiva, Olivier Ribaux:
Pattern analysis in illicit heroin seizures: a novel application of machine learning algorithms. ESANN 2006: 665-670 - [c8]Frédéric Ratle, Anne-Laure Terrettaz-Zufferey, Mikhail F. Kanevski, Pierre Esseiva, Olivier Ribaux:
Learning Manifolds in Forensic Data. ICANN (2) 2006: 894-903 - 2004
- [j1]Mikhail F. Kanevski, Roman Parkin, Aleksey Pozdnukhov, Vadim Timonin, Michel Maignan, Vasiliy V. Demyanov, Stéphane Canu:
Environmental data mining and modeling based on machine learning algorithms and geostatistics. Environ. Model. Softw. 19(9): 845-855 (2004) - [c7]Mikhail F. Kanevski, Michel Maignan, Georges Piller:
Advanced analysis and modelling tools for spatial environmental data. Case study: indoor radon data in Switzerland. EnviroInfo (1) 2004: 205-214 - [c6]Michel Maignan, Mikhail F. Kanevski, F. Celardin, A. Besson:
Geostatistical and Artificial Neuronal Networks maps of the Texture of the soils of Geneva Canton. EnviroInfo (2) 2004: 388-389 - 2002
- [c5]N. Gilardi, Samy Bengio, Mikhail F. Kanevski:
Conditional Gaussian mixture models for environmental risk mapping. NNSP 2002: 777-786 - 2000
- [c4]Elena Savelieva, Alexey Kravetski, Sergey Chernov, Vasiliy V. Demyanov, Vadim Timonin, Rafael V. Arutyunyan, Leonid Aleksandrovich Bolshov, Mikhail F. Kanevski:
Application of MLP and stochastic simulations for electricity load forecasting in Russia. ESANN 2000: 413-418
1990 – 1999
- 1997
- [c3]Mikhail F. Kanevski, Vasiliy V. Demyanov, Michel Maignan:
Mapping of Soil Contamination by Using Artificial Neural Networks and Multivariate Geostatistics. ICANN 1997: 1125-1130 - 1994
- [c2]Rafael V. Arutyunyan, Leonid Aleksandrovich Bolshov, Vasilij M. Goloviznin, S. A. Kabalevski, Mikhail F. Kanevski, Vladimir P. Kiselev, Igor Innokentevich Linge, A. N. Serov:
Development of Specialized Geographical Information Systems for the Analysis of Large Scale Radioecological Accidents. IGIS 1994: 109-112 - [c1]Igor Innokentevich Linge, Rafael V. Arutyunyan, Leonid Aleksandrovich Bolshov, Mikhail F. Kanevski, Vladimir P. Kiselev, Igor A. Osipjanc:
Development of Database Management for the Analysis of Large Scale Radioecological Accidents. SSDBM 1994: 291
Coauthor Index
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