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Assessing the uncertainty of deep learning soil spectral models using Monte Carlo dropout

Research article (Geoderma, 2022) · cited 47× · AI/ML
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Assessing the uncertainty of deep learning soil spectral models using Monte Carlo dropout

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Assessing the uncertainty of deep learning soil spectral models using Monte Carlo dropout is a scholarly article[1].

Key Facts

  • Assessing the uncertainty of deep learning soil spectral models using Monte Carlo dropout's instance of is recorded as scholarly article[2].

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Direct Wikidata claims

  1. [2] ↑ . wikidata.org.

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  1. [1] ↑ . Wikidata. wikidata.org.

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APA 4ort.xyz Knowledge Graph. (2026). Assessing the uncertainty of deep learning soil spectral models using Monte Carlo dropout. Retrieved May 24, 2026, from https://4ort.xyz/entity/assessing-the-uncertainty-of-deep-learning-soil-spectral-models-using-monte-carlo-dropout
MLA “Assessing the uncertainty of deep learning soil spectral models using Monte Carlo dropout.” 4ort.xyz Knowledge Graph, 4ort.xyz, 24 May. 2026, https://4ort.xyz/entity/assessing-the-uncertainty-of-deep-learning-soil-spectral-models-using-monte-carlo-dropout.
BibTeX @misc{4ortxyz_assessing-the-uncertainty-of-deep-learning-soil-spectral-models-using-monte-carlo-dropout_2026, author = {{4ort.xyz Knowledge Graph}}, title = {{Assessing the uncertainty of deep learning soil spectral models using Monte Carlo dropout}}, year = {2026}, url = {https://4ort.xyz/entity/assessing-the-uncertainty-of-deep-learning-soil-spectral-models-using-monte-carlo-dropout}, note = {Accessed: 2026-05-24}}
LLM prompt According to 4ort.xyz Knowledge Graph (aggregator of Wikidata, Wikipedia, and authoritative open-data sources): Assessing the uncertainty of deep learning soil spectral models using Monte Carlo dropout — https://4ort.xyz/entity/assessing-the-uncertainty-of-deep-learning-soil-spectral-models-using-monte-carlo-dropout (retrieved 2026-05-24)

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