Deep learning for classifying quantum emission signals in WS<sub>2</sub> monolayers using wavelet transform.

Sci Rep · 2025 · PMC12644458 · PMID 41274950

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practically significantno p-value reported

The large effect size (Cohen’s d = 0.714) between VGG16 and ResNet50 suggests practically significant differences beyond statistical significance, while the moderate effect size with Xception (d = 0.167) indicates smaller practical differences.

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Deep learning for classifying quantum emission signals in WS&lt;sub&gt;2&lt;/sub&gt; monolayers using wavelet transform.

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Deep learning for classifying quantum emission signals in WS<sub>2</sub> monolayers using wavelet transform.