Drusch, M.
* 2014: Clarifications on the Comparison Between SMOS, VUA, ASCAT, and ECMWF Soil Moisture Products Over Four Watersheds in U.S.
* 2015: Copula-Based Downscaling of Coarse-Scale Soil Moisture Observations With Implicit Bias Correction
* 2015: Soil Moisture Retrieval Using Neural Networks: Application to SMOS
* 2016: L-Band Relative Permittivity of Organic Soil Surface Layers: A New Dataset of Resonant Cavity Measurements and Model Evaluation
* 2016: Long Term Global Surface Soil Moisture Fields Using an SMOS-Trained Neural Network Applied to AMSR-E Data
* 2016: Review of Thermal Infrared Applications and Requirements for Future High-Resolution Sensors
* 2017: FLuorescence EXplorer Mission Concept: ESA's Earth Explorer 8, The
* 2017: Fluorescence Imaging Spectrometer (FLORIS) for ESA FLEX Mission
* 2017: L-Band Relative Permittivity of Organic Soil Surface Layers: A New Dataset of Resonant Cavity Measurements and Model Evaluation
* 2018: Effect of Three Different Data Fusion Approaches on the Quality of Soil Moisture Retrievals from Multiple Passive Microwave Sensors, The
* 2018: Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review
* 2019: Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review
* 2019: Spectral Fitting Algorithm to Retrieve the Fluorescence Spectrum from Canopy Radiance, A
* 2020: Impact of SMOS Soil Moisture Data Assimilation within the Operational Global Flood Awareness System (GloFAS), The
Includes: Drusch, M. Drusch, M.[Matthias]
14 for Drusch, M.
Drusinsky, D.[Doron]
* 2021: Multiagent Pathfinding Under Rigid, Optimization, and Uncertainty Constraints
* 2022: Cryptographic-Biometric Self-Sovereign Personal Identities
Druskin, V.[Vladimir]
* 2016: Direct, Nonlinear Inversion Algorithm for Hyperbolic Problems via Projection-Based Model Reduction
* 2018: Nonlinear Method for Imaging with Acoustic Waves Via Reduced Order Model Backprojection, A
* 2020: Reduced Order Model Approach to Inverse Scattering
* 2024: Reduced Order Modeling Inversion of Monostatic Data in a Multi-scattering Environment