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Mahdi Khodadadzadeh
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2020 – today
- 2024
- [c20]Mahdi Khodadadzadeh, Peter Kalverla, Raúl Zurita-Milla:
Harmonizing Machine Learning Based Phenological Modeling: A Unified Workflow for Comparative Analyses. IGARSS 2024: 5333-5336 - [c19]Mejdi Kaddour, Lucas De Oto, Amel Faiza Tandjaoui, Hachem Guerid, Mahdi Khodadadzadeh:
Analysis of Desertification Trends in the Algerian Steppe Using Multitemporal Satellite Imagery for the Period 2002-2022. IGARSS 2024: 10277-10280 - [i2]Yanwen Wang, Mahdi Khodadadzadeh, Raúl Zurita-Milla:
On the use of adversarial validation for quantifying dissimilarity in geospatial machine learning prediction. CoRR abs/2404.12575 (2024) - 2023
- [j17]Yanwen Wang
, Mahdi Khodadadzadeh
Spatial+: A new cross-validation method to evaluate geospatial machine learning models. Int. J. Appl. Earth Obs. Geoinformation 121: 103364 (2023) - 2022
- [j16]Saeed Soltani-Mohammadi, Fatemeh Sadat Hoseinian, Maliheh Abbaszadeh, Mahdi Khodadadzadeh:
Grade estimation using a hybrid method of back-propagation artificial neural network and particle swarm optimization with integrated samples coordinate and local variability. Comput. Geosci. 159: 104981 (2022) - 2021
- [j15]Isabel Cecilia Contreras Acosta
Resolution Enhancement for Drill-Core Hyperspectral Mineral Mapping. Remote. Sens. 13(12): 2296 (2021) - 2020
- [j14]Laura Tusa, Mahdi Khodadadzadeh
Drill-Core Mineral Abundance Estimation Using Hyperspectral and High-Resolution Mineralogical Data. Remote. Sens. 12(7): 1218 (2020) - [j13]Kasra Rafiezadeh Shahi
Hierarchical Sparse Subspace Clustering (HESSC): An Automatic Approach for Hyperspectral Image Analysis. Remote. Sens. 12(15): 2421 (2020) - [j12]Isabel Cecilia Contreras Acosta
Drill-Core Hyperspectral and Geochemical Data Integration in a Superpixel-Based Machine Learning Framework. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 13: 4214-4228 (2020)
2010 – 2019
- 2019
- [j11]Bikram Koirala
A Supervised Method for Nonlinear Hyperspectral Unmixing. Remote. Sens. 11(20): 2458 (2019) - [j10]Sandra Lorenz
Multi-Sensor Spectral Imaging of Geological Samples: A Data Fusion Approach Using Spatio-Spectral Feature Extraction. Sensors 19(12): 2787 (2019) - [j9]Shuyuan Xu
Abundance-Indicated Subspace for Hyperspectral Classification With Limited Training Samples. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 12(4): 1265-1278 (2019) - [j8]Isabel Cecilia Contreras Acosta
A Machine Learning Framework for Drill-Core Mineral Mapping Using Hyperspectral and High-Resolution Mineralogical Data Fusion. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 12(12): 4829-4842 (2019) - [j7]Ana-Maria Ilisei
An Automatic Method for Subglacial Lake Detection in Ice Sheet Radar Sounder Data. IEEE Trans. Geosci. Remote. Sens. 57(6): 3252-3270 (2019) - [c18]Mahdi Khodadadzadeh, Richard Gloaguen:
Upscaling High-Resolution Mineralogical Analyses to Estimate Mineral Abundances in Drill Core Hyperspectral Data. IGARSS 2019: 1845-1848 - [c17]Cecilia Contreras, Mahdi Khodadadzadeh, Pedram Ghamisi, Richard Gloaguen:
Mineral Mapping of Drill Core Hyperspectral Data with Extreme Learning Machines. IGARSS 2019: 2686-2689 - [c16]Richard Gloaguen, Margret C. Fuchs, Mahdi Khodadadzadeh, Pedram Ghamisi, Moritz Kirsch, René Booysen
Multi-Source and multi-Scale Imaging-Data Integration to boost Mineral Mapping. IGARSS 2019: 5587-5589 - [c15]Cecilia Contreras, Mahdi Khodadadzadeh, Laura Tusa, Christina Loidolt, Raimon Tolosana-Delgado, Richard Gloaguen:
Geochemical And Hyperspectral Data Fusion For Drill-Core Mineral Mapping. WHISPERS 2019: 1-4 - [c14]Bikram Koirala, Zohreh Zahiri, Mahdi Khodadadzadeh, Paul Scheunders
Fractional Abundance Estimation of Mixed and Compound Materials by Hyperspectral Imaging. WHISPERS 2019: 1-5 - [c13]Kasra Rafiezadeh Shahi
The Application Of Subspace Clustering Algorithms In Drill-Core Hyperspectral Domaining. WHISPERS 2019: 1-5 - 2018
- [j6]Moritz Kirsch
Integration of Terrestrial and Drone-Borne Hyperspectral and Photogrammetric Sensing Methods for Exploration Mapping and Mining Monitoring. Remote. Sens. 10(9): 1366 (2018) - [c12]Laura Tusa, Louis Andreani
Extraction of Structural and Mineralogical Features from Hyperspectral Drill-Core Scans. IGARSS 2018: 4070-4073 - [c11]Mahdi Khodadadzadeh, Pedram Ghamisi, Cecilia Contreras, Richard Gloaguen:
Subspace Multinomial Logistic Regression Ensemble for Classification of Hyperspectral Images. IGARSS 2018: 5740-5743 - [c10]Ana-Maria Ilisei, Mahdi Khodadadzadeh, Lorenzo Bruzzone:
Extraction of Statistical Features for Improved Automatic Detection of Subglacial Lakes in Radar Sounder Data. IGARSS 2018: 6792-6795 - [c9]Richard Gloaguen, Pedram Ghamisi, Sandra Lorenz
The Need for Multi-Source, Multi-Scale Hyperspectral Imaging to Boost Non-Invasive Mineral Exploration. IGARSS 2018: 7430-7433 - [c8]Cecilia Contreras
A Machine Learning Technique for Drill Core Hyperspectral Data Analysis. WHISPERS 2018: 1-5 - 2017
- [c7]Mahdi Khodadadzadeh, Ana-Maria Ilisei, Lorenzo Bruzzone:
A technique based on adaptive windows for the classification of radar sounder data. IGARSS 2017: 3739-3742 - 2016
- [j5]Jun Li
A Discontinuity Preserving Relaxation Scheme for Spectral-Spatial Hyperspectral Image Classification. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 9(2): 625-639 (2016) - [c6]Mahdi Khodadadzadeh, Lorenzo Bruzzone, Jun Li
A Gaussian approach to subspace based classification of hyperspectral images. IGARSS 2016: 3278-3281 - 2015
- [j4]Lianru Gao, Jun Li
Subspace-Based Support Vector Machines for Hyperspectral Image Classification. IEEE Geosci. Remote. Sens. Lett. 12(2): 349-353 (2015) - [j3]Mahdi Khodadadzadeh, Jun Li
Fusion of Hyperspectral and LiDAR Remote Sensing Data Using Multiple Feature Learning. IEEE J. Sel. Top. Appl. Earth Obs. Remote. Sens. 8(6): 2971-2983 (2015) - [c5]Mahdi Khodadadzadeh, Aurora Cuartero
Fusion of hyperspectral and lidar data using generalized composite kernels: A case study in Extremadura, Spain. IGARSS 2015: 61-64 - [c4]Mahdi Khodadadzadeh, Jun Li, Antonio Plaza
Hyperspectral image classification based on union of subspaces. JURSE 2015: 1-4 - 2014
- [j2]Mahdi Khodadadzadeh, Jun Li
A Subspace-Based Multinomial Logistic Regression for Hyperspectral Image Classification. IEEE Geosci. Remote. Sens. Lett. 11(12): 2105-2109 (2014) - [j1]Mahdi Khodadadzadeh, Jun Li
Spectral-Spatial Classification of Hyperspectral Data Using Local and Global Probabilities for Mixed Pixel Characterization. IEEE Trans. Geosci. Remote. Sens. 52(10): 6298-6314 (2014) - [c3]Mahdi Khodadadzadeh, Jun Li
A new framework for hyperspectral image classification using multiple spectral and spatial features. IGARSS 2014: 4628-4631 - [c2]Jun Li, Yi Liu, Antonio Plaza
Spectrometer-driven spectral partitioning for hyperspectral image classification. WHISPERS 2014: 1-4 - 2013
- [c1]Mahdi Khodadadzadeh, Jun Li
Spectral-spatial classification for hyperspectral data using SVM and subspace MLR. IGARSS 2013: 2180-2183 - 2011
- [i1]Roozbeh Rajabi, Mahdi Khodadadzadeh, Hassan Ghassemian:
Graph Regularized Nonnegative Matrix Factorization for Hyperspectral Data Unmixing. CoRR abs/1111.0885 (2011)
Coauthor Index
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last updated on 2024-10-07 21:21 CEST by the dblp team
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