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/assets?dynamic_filters%5Barticle_title%5D=A+Machine%E2%80%90Learning+Approach+to+Classify+Cloud%E2%80%90to%E2%80%90Ground+and+Intracloud+Lightning&template=grid

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- grl61706-tbl-0001
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- John Wiley & Sons, Inc.
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Article Title: A Machine‐Learning Approach to Classify Cloud‐to‐Ground and Intracloud Lightning
Publication Title: Geophysical Research Letters

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- grl61706-fig-0001
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- John Wiley & Sons, Inc.
Description (a) RMS vertical location errors and (b) maximum located source altitude for CG sources at ground level (z = 0). The locations of 10 CAMMA stations are marked by white dots. The 1,200‐m RMS...
Article Title: A Machine‐Learning Approach to Classify Cloud‐to‐Ground and Intracloud Lightning
Publication Title: Geophysical Research Letters

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- grl61706-tbl-0002
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- John Wiley & Sons, Inc.
Description Table
Article Title: A Machine‐Learning Approach to Classify Cloud‐to‐Ground and Intracloud Lightning
Publication Title: Geophysical Research Letters

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- grl61706-fig-0002
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- John Wiley & Sons, Inc.
Description Waveforms for two −CG pulses in panels (a and b) and two −IC pulses in panels (c and d). In each row, one pulse was correctly classified by our model and the other was misclassified. The...
Article Title: A Machine‐Learning Approach to Classify Cloud‐to‐Ground and Intracloud Lightning
Publication Title: Geophysical Research Letters

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- grl61706
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- John Wiley & Sons, Inc.
Description A Machine‐Learning Approach to Classify Cloud‐to‐Ground and Intracloud LightningZhu et al. - Geophysical Research LettersGeophys Res Lett vol. 48, 16 January 2021
Article Title: A Machine‐Learning Approach to Classify Cloud‐to‐Ground and Intracloud Lightning
Publication Title: Geophysical Research Letters

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