Automatic identification of saltating tracks driven by strong wind in high-speed video using multiple statistical quantities of instant particle velocity

2024/09/21 by Hongji Zhou, Fanmin Mei, Chuan Lin +5 · 1 voice
Earth and Planetary Sciences · Environmental Science · #Aeolian processes and effects #Hydrology and Sediment Transport Processes #Remote Sensing and LiDAR Applications

paper · doi:10.1016/j.aeolia.2024.100940

openalex publication_date 2024/09/21 · crossref created 2024/09/21 · crossref issued 2024/12/01 · crossref published 2024/12/01 · crossref published-print 2024/12/01 · crossref deposited 2024/12/03 · crossref indexed 2025/07/14 · openalex created_date 2025/10/10 · openalex updated_date 2026/06/15

Citations

• Stacked generalization
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• The advantages of the Matthews correlation coefficient (MCC) over F1 score and accuracy in binary classification evaluation
• Mineral dust aerosol impacts on global climate and climate change
• Sediment texture and geochemistry as predictors of sub-depositional environment in a modern estuary using machine learning: A framework for investigating clay-coated sand grains
• Stochastic Games

Discussions

• Zhou et al., Aeolian Research; Automatic identification of saltating tracks driven by strong wind in high-speed video using multiple statistical quantities of instant particle velocity doi.org/10.1016 [bsky, 0 points, 0 comments]