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classification models » classification model (Expand Search)
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classification models » classification model (Expand Search)
image classification » _ classification (Expand Search)
increase decrease » increased release (Expand Search)
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Classification process.
Published 2024“…The experimental results in ResNet34 show that the classification accuracy of the dataset before and after RGB reconstruction increases from 88.87% to 91.75%, demonstrating that RGB image reconstruction can strengthen image features; ResNet18, ResNet34, ResNet50, ResNet101, CBAM-ResNet34, SENet-ResNet34, and SENet-ResNet34-DCN models have classification accuracies of 72.25%, 91.75%, 89%, 88.48%, 92.28%, 92.80%, and 94.24%, respectively.SENet-ResNet34-DCN achieves the greatest classification accuracy results, with a model loss of roughly 0.3. …”
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Proteins from volcano plot which had notable increases or decreases listed in order of greatest to least significance (adjusted p-values).
Published 2022“…<p>Proteins from volcano plot which had notable increases or decreases listed in order of greatest to least significance (adjusted p-values).…”
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Comparison of image classification models in heavy and light traffic.
Published 2025“…<p>Comparison of image classification models in heavy and light traffic.…”
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Performance metrics comparison analysis of image classification models.
Published 2025“…<p>Performance metrics comparison analysis of image classification models.</p>…”
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Comparison of image classification models in rural and urban roads.
Published 2025“…<p>Comparison of image classification models in rural and urban roads.…”
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Comparison of image classification models in Straight and Zigzag roads.
Published 2025“…<p>Comparison of image classification models in Straight and Zigzag roads.…”
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