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Alessandro Lapini
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2020 – today
- 2023
- [j11]Alessandro Lapini
, Ada Vittoria Bosisio
An Antenna Pattern Correction Algorithm for Conical Scanning Spaceborne Radiometers: The CIMR Case. IEEE Trans. Geosci. Remote. Sens. 61: 1-15 (2023) - [c23]Fabrizio Baroni
Combining the Strong Fluctuation Theory with Rough Soil Models for Improving the Simulation Accuracy of Alpine Snowpacks at C- and X-Bands. IGARSS 2023: 9-12 - [c22]Emanuele Santi, Simonetta Paloscia, Simone Pettinato, Alessandro Lapini, Giacomo Fontanelli, Fabrizio Baroni
High Resolution Mapping of Crop Biomass by Combining Sentinel-1 and Cosmo Skymed Through Machine Learning. IGARSS 2023: 1501-1504 - 2022
- [j10]Marco Brogioni
Preliminary Studies on CIMR Antenna Pattern Brightness Temperature Compensation. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15: 173-183 (2022) - [j9]Giacomo Fontanelli
Early-Season Crop Mapping on an Agricultural Area in Italy Using X-Band Dual-Polarization SAR Satellite Data and Convolutional Neural Networks. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 15: 6789-6803 (2022) - [j8]Simone Pilia
On the Relationship Between Stickiness in DMRT Theory and Physical Parameters of Snowpack: Theoretical Formulation and Experimental Validation With SNOWPACK Snow Model and X-Band SAR Data. IEEE Trans. Geosci. Remote. Sens. 60: 1-14 (2022) - [c21]Simone Pettinato, Giuliano Ramat, N. Souissi, Fabrizio Baroni
The Application of COSMO-Skymed Images to Agricultural Management in Central Tunisia. IGARSS 2022: 4747-4749 - [c20]Emanuele Santi
High Resolution Mapping of Vegetation Biomass and Soil Moisture by Using AMSR2, Sentinel-1 and Machine Learning. IGARSS 2022: 4943-4946 - [c19]Simonetta Paloscia, Emanuele Santi
A Method for Estimating Agricultural Crop Biomass by Using Sar Images at X and C Bands. IGARSS 2022: 4947-4950 - [c18]Simonetta Paloscia, Emanuele Santi
Multifrequency SAR Data for Estimating Snow, Soil and Vegetation Parameters. IGARSS 2022: 5180-5183 - 2021
- [j7]Emanuele Santi
Mapping Woody Volume of Mediterranean Forests by Using SAR and Machine Learning: A Case Study in Central Italy. Remote. Sens. 13(4): 809 (2021) - [c17]Fabrizio Baroni
Integration of DMRT and SNOWPACK Models for Simulating Backscattering and Comparison with COSMO-SkyMed Data. IGARSS 2021: 5477-5480 - [c16]Alessandro Lapini
Crop Classification and Biomass Estimate Using Cosmo-Skymed and Sentinel-1 Data in an Agricultural Test Area in Central Italy. IGARSS 2021: 5933-5936 - 2020
- [j6]Alessandro Lapini
Comparison of Machine Learning Methods Applied to SAR Images for Forest Classification in Mediterranean Areas. Remote. Sens. 12(3): 369 (2020) - [c15]Alessandro Lapini
Application of Deep Learning to Optical and SAR Images for the Classification of Agricultural Areas in Italy. IGARSS 2020: 4163-4166
2010 – 2019
- 2018
- [j5]Francesco Buonamici
Reverse engineering of mechanical parts: A template-based approach. J. Comput. Des. Eng. 5(2): 145-159 (2018) - [c14]Alessandro Lapini
Audio Virtualization of Facade Acoustic Insulation by Convex Optimization. EUSIPCO 2018: 2185-2189 - 2016
- [j4]Alessandro Lapini
The Normalized Differential Spectral Sensitivity Approach Applied to the Retrieval of Tropospheric Water Vapor Fields Using a Constellation of Corotating LEO Satellites. IEEE Trans. Geosci. Remote. Sens. 54(1): 135-152 (2016) - [c13]Alessandro Lapini
Active noise control for pulse signals by wave field synthesis. EUSIPCO 2016: 883-887 - 2014
- [j3]Alessandro Lapini
Blind Speckle Decorrelation for SAR Image Despeckling. IEEE Trans. Geosci. Remote. Sens. 52(2): 1044-1058 (2014) - [c12]Alessandro Lapini
Tomographic techniques for the retrieval of tropospheric water vapour fields by using co-rotating LEO satellites. ICASSP 2014: 8124-8128 - [c11]Alessandro Lapini
Retrieval of 2-D tropospheric water vapour fields by using a constellation of co-rotating LEO satellites. IGARSS 2014: 4994-4997 - [c10]Alessandro Lapini, Fabrizio Argenti, Alessandro Piva, Luca Bencini:
Comparison of super-resolution methods for quality enhancement of digital biomedical images. ISMICT 2014: 1-5 - [c9]Francescopaolo Sica, Luciano Alparone
Benefits of blind speckle decorrelation for InSAR processing. SAR 2014: 92430D - 2013
- [j2]Tiziano Bianchi
Amplitude vs intensity Bayesian despeckling in the wavelet domain for SAR images. Digit. Signal Process. 23(5): 1353-1362 (2013) - 2012
- [j1]Fabrizio Argenti
Fast MAP Despeckling Based on Laplacian-Gaussian Modeling of Wavelet Coefficients. IEEE Geosci. Remote. Sens. Lett. 9(1): 13-17 (2012) - [c8]Alessandro Lapini, Tiziano Bianchi, Fabrizio Argenti, Luciano Alparone:
A whitening method for the despeckling of SAR images affected by correlated speckle noise. EUSIPCO 2012: 2487-2491 - [c7]Luciano Alparone
Multiresolution map despeckling of COSMO-SkyMed images. IGARSS 2012: 5490-5493 - [c6]Bruno Aiazzi
An experimental setup for multiresolution despeckling of COSMO-SkyMed image products. SAR 2012: 853603 - [c5]Tiziano Bianchi
Amplitude vs intensity despeckling in the wavelet domain using bayesian estimators. TyWRRS 2012: 267-274 - 2011
- [c4]Fabrizio Argenti, Tiziano Bianchi, Alessandro Lapini, Luciano Alparone:
Simplified MAP despeckling based on Laplacian-Gaussian modeling of undecimated wavelet coefficients. EUSIPCO 2011: 1140-1144 - [c3]Fabrizio Argenti
Bayesian despeckling of SAR images based on Laplacian-Gaussian modeling of undecimatedwavelet coefficients. ICASSP 2011: 1445-1448 - [c2]Bruno Aiazzi
An unsupervised method for quality assessment of despeckling: an evaluation on COSMO-SkyMed data. SAR 2011: 81790D - 2010
- [c1]Luciano Alparone
An evaluation of Bayesian estimators and PDF models for despeckling in the undecimated wavelet domain. SAR 2010: 782902
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