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AL-Tameemi, Ahmed A.; Li, Fusheng; Xiao, Zenan; Raza, Ghalib (2026) Advancements in machine learning, deep learning, and data fusion techniques for XRF spectrometry in heavy metal detection: a critical review. Journal of Analytical Atomic Spectrometry, 41 (4). doi:10.1039/d5ja00458f

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Reference TypeJournal (article/letter/editorial)
TitleAdvancements in machine learning, deep learning, and data fusion techniques for XRF spectrometry in heavy metal detection: a critical review
JournalJournal of Analytical Atomic Spectrometry
AuthorsAL-Tameemi, Ahmed A.Author
Li, FushengAuthor
Xiao, ZenanAuthor
Raza, GhalibAuthor
Year2026Volume41
Issue4
PublisherRoyal Society of Chemistry (RSC)
DOIdoi:10.1039/d5ja00458fSearch in ResearchGate
Generate Citation Formats
Mindat Ref. ID19851054Long-form Identifiermindat:1:5:19851054:5
GUID0
Full ReferenceAL-Tameemi, Ahmed A.; Li, Fusheng; Xiao, Zenan; Raza, Ghalib (2026) Advancements in machine learning, deep learning, and data fusion techniques for XRF spectrometry in heavy metal detection: a critical review. Journal of Analytical Atomic Spectrometry, 41 (4). doi:10.1039/d5ja00458f
Plain TextAL-Tameemi, Ahmed A.; Li, Fusheng; Xiao, Zenan; Raza, Ghalib (2026) Advancements in machine learning, deep learning, and data fusion techniques for XRF spectrometry in heavy metal detection: a critical review. Journal of Analytical Atomic Spectrometry, 41 (4). doi:10.1039/d5ja00458f
In(2026) Journal of Analytical Atomic Spectrometry Vol. 41 (4). Royal Society of Chemistry (RSC)

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