يعرض 1 - 10 نتائج من 814 نتيجة بحث عن '"geochemical data"', وقت الاستعلام: 1.46s تنقيح النتائج
  1. 1
    دورية أكاديمية
    Mineral Prospectivity Prediction Based on Self-Supervised Contrastive Learning and Geochemical Data: A Case Study of the Gold Deposit in the Malanyu District, Hebei Province, China

    المؤلفون: Miao, Qunfeng, Wang, Pan, Zhao, HengqianAff2, Aff3, IDs11053024103353_cor3, Li, Zhibin, Qi, Yunfei, Mao, Jihua, Li, Meiyu, Tang, Guanglong

    المصدر: Natural Resources Research: Official Journal of the International Association for Mathematical Geosciences. 33(4):1377-1391

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  2. 2
    دورية أكاديمية
    Denoising of Geochemical Data using Deep Learning–Implications for Regional Surveys

    المؤلفون: Zhang, Steven E.Aff1, IDs11053024103175_cor1, Bourdeau, Julie E., Nwaila, Glen T., Parsa, Mohammad, Ghorbani, Yousef

    المصدر: Natural Resources Research: Official Journal of the International Association for Mathematical Geosciences. 33(2):495-520

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  3. 3
    Deriving big geochemical data from high-resolution remote sensing data via machine learning: Application to a tailing storage facility in the Witwatersrand goldfields

    المؤلفون: Zhang, Steven E., Nwaila, Glen T., Bourdeau, Julie E., Ghorbani, Yousef, Carranza, Emmanuel John M.

    المصدر: Artificial Intelligence in Geosciences. 4:9-21

    مصطلحات موضوعية: Big geochemical data, Dry labs, Machine learning, Remote sensing, Tailing storage facilities, Witwatersrand Basin, Mineral Processing, Mineralteknik, Centrumbildning - Centrum för avancerad gruvteknik och metallurgi (CAMM), Centre - Centre for Advanced Mining & Metallurgy (CAMM)

    وصف الملف: electronic

    URL الوصول: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-96375
    https://doi.org/10.1016/j.aiig.2023.01.005
    https://ltu.diva-portal.org/smash/get/diva2:1750238/FULLTEXT01.pdf

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  4. 4
    دورية أكاديمية
    Big geochemical data through remote sensing for dynamic mineral resource monitoring in tailing storage facilities

    المؤلفون: Steven E. Zhang, Glen T. Nwaila, Shenelle Agard, Julie E. Bourdeau, Emmanuel John M. Carranza, Yousef Ghorbani

    المصدر: Artificial Intelligence in Geosciences, Vol 4, Iss , Pp 137-149 (2023)

    مصطلحات موضوعية: Big geochemical data, Mine waste valorisation, Tailings storage facilities, Sentinel-2, Remote sensing, Machine learning, Geography (General), G1-922, Information technology, T58.5-58.64

    وصف الملف: electronic resource

    Relation: http://www.sciencedirect.com/science/article/pii/S266654412300028X; https://doaj.org/toc/2666-5441

    URL الوصول: https://doaj.org/article/3f12ef98690a45ab9673b30bd1e1666f

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  5. 5
    دورية أكاديمية
    Deriving big geochemical data from high-resolution remote sensing data via machine learning: Application to a tailing storage facility in the Witwatersrand goldfields

    المؤلفون: Steven E. Zhang, Glen T. Nwaila, Julie E. Bourdeau, Yousef Ghorbani, Emmanuel John M. Carranza

    المصدر: Artificial Intelligence in Geosciences, Vol 4, Iss , Pp 9-21 (2023)

    مصطلحات موضوعية: Remote sensing, Big geochemical data, Machine learning, Tailing storage facilities, Witwatersrand Basin, Dry labs, Geography (General), G1-922, Information technology, T58.5-58.64

    وصف الملف: electronic resource

    Relation: http://www.sciencedirect.com/science/article/pii/S2666544123000059; https://doaj.org/toc/2666-5441

    URL الوصول: https://doaj.org/article/8c2410056b5241adb33d298d8ab061f1

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  6. 6
    مؤتمر
    Interpolation of Geochemical Data with Aster Images Based on AlexNet Convolution Neural Network

    المؤلفون: Bai, Shi, Zhao, Jie

    المصدر: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium Geoscience and Remote Sensing Symposium, IGARSS 2020 - 2020 IEEE International. :244-247 Sep, 2020

    Relation: IGARSS 2020 - 2020 IEEE International Geoscience and Remote Sensing Symposium

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  7. 7
    دورية أكاديمية
    Geochemical soil survey for gold in Ogudu-Ogbagba Area, Osun State, southwestern Nigeria

    المؤلفون: Salami, Mudasiru, Adetunji, AdemuyiwaAff1, IDs12517023118213_cor2, Olorunfemi, Akintunde Olarewaju, Alao-Daniel, Adedamola Beatrice, Adesiyan, Taohoreed Adewale

    المصدر: Arabian Journal of Geosciences. 17(1)

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  8. 8
    مؤتمر
    Geochemical And Hyperspectral Data Fusion For Drill-Core Mineral Mapping

    المؤلفون: Contreras, Cecilia, Khodadadzadeh, Mahdi, Tusa, Laura, Loidolt, Christina, Tolosana-Delgado, Raimon, Gloaguen, Richard

    المصدر: 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS) Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS), 2019 10th Workshop on. :1-4 Sep, 2019

    Relation: 2019 10th Workshop on Hyperspectral Imaging and Signal Processing: Evolution in Remote Sensing (WHISPERS)

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  9. 9
    دورية أكاديمية
    Drill-Core Hyperspectral and Geochemical Data Integration in a Superpixel-Based Machine Learning Framework

    المؤلفون: Acosta, I.C.C., Khodadadzadeh, M., Tolosana-Delgado, R., Gloaguen, R.

    المصدر: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing IEEE J. Sel. Top. Appl. Earth Observations Remote Sensing Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of. 13:4214-4228 2020

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  10. 10
    Advanced geochemical exploration knowledge using machine learning: Prediction of unknown elemental concentrations and operational prioritization of Re-analysis campaigns

    المؤلفون: Zhang, Steven E., Bourdeau, Julie E., Nwaila, Glen T., Ghorbani, Yousef

    المصدر: Artificial Intelligence in Geosciences. 3:86-100

    مصطلحات موضوعية: Advanced exploration knowledge, Canada, Geochemical data, Machine learning, Re-purposing legacy data, Mineral Processing, Mineralteknik

    وصف الملف: print

    URL الوصول: https://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-94288
    https://doi.org/10.1016/j.aiig.2022.10.003

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