Zobrazeno 1 - 10
of 60
pro vyhledávání: '"Mahdi Khodadadzadeh"'
Publikováno v:
International Journal of Applied Earth Observations and Geoinformation, Vol 121, Iss , Pp 103364- (2023)
Random cross-validation (CV) is often used to evaluate geospatial machine learning models, particularly when a limited amount of sample data are available, and collecting an extra test set is unfeasible. However, the prediction locations can be subst
Externí odkaz:
https://doaj.org/article/bdfb2e79c9764a5c994adc0a41d89079
Autor:
Isabel Cecilia Contreras Acosta, Mahdi Khodadadzadeh, Raimon Tolosana-Delgado, Richard Gloaguen
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, Vol 13, Pp 4214-4228 (2020)
The analysis of drill-core samples is one of the most important steps in the mining industry for the exploration and discovery of mineral resources. Geochemical assays are a common approach to represent the abundance of different chemical elements an
Externí odkaz:
https://doaj.org/article/6f3405046b6d43f3ba10cd5d2c9a8e94
Publikováno v:
Remote Sensing, Vol 13, Iss 12, p 2296 (2021)
Drill-core samples are a key component in mineral exploration campaigns, and their rapid and objective analysis is becoming increasingly important. Hyperspectral imaging of drill-cores is a non-destructive technique that allows for non-invasive and f
Externí odkaz:
https://doaj.org/article/a972702624fa4e87957f8fc2bc4f3a81
Autor:
Kasra Rafiezadeh Shahi, Mahdi Khodadadzadeh, Laura Tusa, Pedram Ghamisi, Raimon Tolosana-Delgado, Richard Gloaguen
Publikováno v:
Remote Sensing, Vol 12, Iss 15, p 2421 (2020)
Hyperspectral imaging techniques are becoming one of the most important tools to remotely acquire fine spectral information on different objects. However, hyperspectral images (HSIs) require dedicated processing for most applications. Therefore, seve
Externí odkaz:
https://doaj.org/article/35695b723b9d4f609c177b16d8949984
Autor:
Laura Tuşa, Mahdi Khodadadzadeh, Cecilia Contreras, Kasra Rafiezadeh Shahi, Margret Fuchs, Richard Gloaguen, Jens Gutzmer
Publikováno v:
Remote Sensing, Vol 12, Iss 7, p 1218 (2020)
Due to the extensive drilling performed every year in exploration campaigns for the discovery and evaluation of ore deposits, drill-core mapping is becoming an essential step. While valuable mineralogical information is extracted during core logging
Externí odkaz:
https://doaj.org/article/c8059a9d60aa48c9af483042a9355319
Autor:
Bikram Koirala, Mahdi Khodadadzadeh, Cecilia Contreras, Zohreh Zahiri, Richard Gloaguen, Paul Scheunders
Publikováno v:
Remote Sensing, Vol 11, Iss 20, p 2458 (2019)
Due to the complex interaction of light with the Earth’s surface, reflectance spectra can be described as highly nonlinear mixtures of the reflectances of the material constituents occurring in a given resolution cell of hyperspectral data. Our aim
Externí odkaz:
https://doaj.org/article/59f949caa7814f4bbefed88cec88da7a
Autor:
Sandra Lorenz, Peter Seidel, Pedram Ghamisi, Robert Zimmermann, Laura Tusa, Mahdi Khodadadzadeh, I. Cecilia Contreras, Richard Gloaguen
Publikováno v:
Sensors, Vol 19, Iss 12, p 2787 (2019)
Rapid, efficient and reproducible drillcore logging is fundamental in mineral exploration. Drillcore mapping has evolved rapidly in the recent decade, especially with the advances in hyperspectral spectral imaging. A wide range of imaging sensors is
Externí odkaz:
https://doaj.org/article/552bd19b3b5443e0922cabd09c773ae7
Autor:
Moritz Kirsch, Sandra Lorenz, Robert Zimmermann, Laura Tusa, Robert Möckel, Philip Hödl, René Booysen, Mahdi Khodadadzadeh, Richard Gloaguen
Publikováno v:
Remote Sensing, Vol 10, Iss 9, p 1366 (2018)
Mapping lithology and geological structures accurately remains a challenge in difficult terrain or in active mining areas. We demonstrate that the integration of terrestrial and drone-borne multi-sensor remote sensing techniques significantly improve
Externí odkaz:
https://doaj.org/article/2340d875f0d14dc78207aec8ec56805f
Publikováno v:
International Society for Photogrammetry and Remote Sensing (ISPRS), 31.08.-02.09.2020, Nice, FranceISPRS Archives, 43(B3),pp. 383-388
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2020, Pp 383-388 (2020)
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLIII-B3-2020, Pp 383-388 (2020)
A multi-label classification concept is introduced for the mineral mapping task in drill-core hyperspectral data analysis. As opposed to traditional classification methods, this approach has the advantage of considering the different mineral mixtures
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ad0530f16f8401e600556373a65b20ba
https://doi.org/10.5194/isprs-archives-xliii-b3-2020-383-2020
https://doi.org/10.5194/isprs-archives-xliii-b3-2020-383-2020
Autor:
Isabel Cecilia Contreras Acosta, Mahdi Khodadadzadeh, Pedram Ghamisi, Laura Tusa, Richard Gloaguen
Publikováno v:
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 12(2020)12, 4829-4842
Mining companies heavily rely on drill-core samples during exploration campaigns as they provide valuable geological information to target important ore accumulations. Traditional core logging techniques are time-consuming and subjective. Hyperspectr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::7a653da5e59885f5bafcba39b5d897fe
https://doi.org/10.1109/jstars.2019.2924292
https://doi.org/10.1109/jstars.2019.2924292