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Geographical discrimination and adulteration analysis for edible oils using two-dimensional correlation spectroscopy and convolutional neural networks (CNNs)
Research article (Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, 2020) · cited 41× · AI/ML
Geographical discrimination and adulteration analysis for edible oils using two-dimensional correlation spectroscopy and convolutional neural networks (CNNs)
Summary
Geographical discrimination and adulteration analysis for edible oils using two-dimensional correlation spectroscopy and convolutional neural networks (CNNs) is a scholarly article[1].
Key Facts
Geographical discrimination and adulteration analysis for edible oils using two-dimensional correlation spectroscopy and convolutional neural networks (CNNs)'s instance of is recorded as scholarly article[2].
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APA4ort.xyz Knowledge Graph. (2026). Geographical discrimination and adulteration analysis for edible oils using two-dimensional correlation spectroscopy and convolutional neural networks (CNNs). Retrieved May 24, 2026, from https://4ort.xyz/entity/geographical-discrimination-and-adulteration-analysis-for-edible-oils-using-two-dimensional-correlation-spectroscopy-and
MLA“Geographical discrimination and adulteration analysis for edible oils using two-dimensional correlation spectroscopy and convolutional neural networks (CNNs).” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/geographical-discrimination-and-adulteration-analysis-for-edible-oils-using-two-dimensional-correlation-spectroscopy-and.
BibTeX@misc{4ortxyz_geographical-discrimination-and-adulteration-analysis-for-edible-oils-using-two-dimensional-correlation-spectroscopy-and_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Geographical discrimination and adulteration analysis for edible oils using two-dimensional correlation spectroscopy and convolutional neural networks (CNNs)}}, year = {2026}, url = {https://4ort.xyz/entity/geographical-discrimination-and-adulteration-analysis-for-edible-oils-using-two-dimensional-correlation-spectroscopy-and}, note = {Accessed: 2026-05-24}}
LLM promptAccording to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Geographical discrimination and adulteration analysis for edible oils using two-dimensional correlation spectroscopy and convolutional neural networks (CNNs) — https://4ort.xyz/entity/geographical-discrimination-and-adulteration-analysis-for-edible-oils-using-two-dimensional-correlation-spectroscopy-and (retrieved 2026-05-24)
