Search alternatives:
larger decrease » marked decrease (Expand Search)
map decrease » mean decrease (Expand Search), a decrease (Expand Search), small decrease (Expand Search)
cnn decrease » nn decrease (Expand Search), mean decrease (Expand Search), a decrease (Expand Search)
_ decrease » _ decreased (Expand Search), _ decreasing (Expand Search)
ai larger » ai large (Expand Search), a large (Expand Search), _ larger (Expand Search)
larger decrease » marked decrease (Expand Search)
map decrease » mean decrease (Expand Search), a decrease (Expand Search), small decrease (Expand Search)
cnn decrease » nn decrease (Expand Search), mean decrease (Expand Search), a decrease (Expand Search)
_ decrease » _ decreased (Expand Search), _ decreasing (Expand Search)
ai larger » ai large (Expand Search), a large (Expand Search), _ larger (Expand Search)
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Displacement cloud map (geology).
Published 2025“…The primary trend indicates an increase in clay content of loess, a decrease in grit content, a relative increase in cohesion, and a relative decrease in the internal friction angle. …”
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CNN framework.
Published 2025“…These models have got a complex optimizer installed on them to decrease the false positive or DDoS case detection efficiency. …”
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CNN frameworks.
Published 2025“…These models have got a complex optimizer installed on them to decrease the false positive or DDoS case detection efficiency. …”
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CNN model.
Published 2025“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
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Architecture of the proposed shallow CNN.
Published 2025“…Classification analysis revealed that ComBat increased average AUC by 15.19%, whereas GAN decreased AUC by 2.56%.</p><p>Conclusion</p><p>While GAN qualitatively enhances image harmonization, ComBat provides superior statistical improvements in feature stability and classification performance, highlighting the importance of robust feature-level harmonization in radiomics.…”
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CNN-LSTM action recognition process.
Published 2025“…According to the experimental results, when the grinding depth increases to 21 μm, the average training loss of the model further decreases to 0.03622, and the surface roughness Ra value significantly decreases to 0.1624 μm. …”
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TITAN decreaser diatom heatmap.
Published 2025“…., <i>z-</i>) diatom taxa (y-axis) to at least one of the five stressors, in decreasing order of number of stressor responses. Blue-orange scale corresponds to the <i>z</i> score that indicates the magnitude of response to a stressor.…”
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