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The influence of training data variability on a supervised machine learning classifier for Structure from Motion (SfM) point clouds of rock slopes
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“The training data construction for ML models accounted for how variability affects model performance.66”
From SEMTWIST Quantification of Biofilm Infection in Human Chronic Wound Using Scanning Electron Microscopy and Machine Learning (2025) · cites this paper as [66]
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Cited by
Sorted by citations
Singh, S., Muniz De Oliveira, F., Wang, C., Kumar, M., Xuan, Y., DeMazumder, D., Sen, C. K., & Roy, S. (2025) · Advances in Wound Care · doi:10.1089/wound.2024.0291 · Cited by 6
Metadata
- Authors
- Weidner, L., & Walton, G.
- Venue
- Engineering Geology
- Publisher
- Elsevier BV
- Published
- 2021-12
- Volume
- 294
- Pages
- 106344
- ISSN
- 0013-7952
- Cited by
- 22
- References
- 0
- Language
- en
- Licence
- Funders
- Colorado Department of Transportation
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- CoChat. (2026). Citation check: The influence of training data variability on a supervised machine learning classifier for Structure from Motion (SfM) point clouds of rock slopes. https://app.cochat.ai/papers/10.1016/j.enggeo.2021.106344
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- Weidner, L., & Walton, G. (2021). The influence of training data variability on a supervised machine learning classifier for Structure from Motion (SfM) point clouds of rock slopes. Engineering Geology. https://doi.org/10.1016/j.enggeo.2021.106344