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Research map / 3D vision / Face and shape

Automated Model Design and Benchmarking of Deep Learning Models for COVID-19 Detection with Chest CT Scans

AAAI 2021 · 3D vision › Face and shape · approach: Learned mesh and geometric representations · 45 citations (OpenAlex)

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Measured effects reported in the paper

What was changedWhereMeasuredEffect
Use DNAS to search a small-scale model instead of the strongest manually designed baseline3D COVID-19 CT classification · Clean-CC-CCII testaccuracy: 87.02 -> 88.55Helped
Use DNAS to search a large-scale model instead of the strongest manually designed baseline3D COVID-19 CT classification · Clean-CC-CCII testaccuracy: 87.02 -> 88.69Helped
Use DNAS to search a small-scale model instead of the strongest manually designed baseline3D COVID-19 CT classification · MosMedData testaccuracy: 81.82 -> 81.17No clear effect
Use DNAS to search a large-scale model instead of the strongest manually designed baseline3D COVID-19 CT classification · MosMedData testaccuracy: 81.82 -> 82.29Helped
Use DNAS to search a small-scale model instead of the strongest manually designed baseline3D COVID-19 CT classification · Covid-CTset testaccuracy: 93.87 -> 94.27Helped
Use DNAS to search a large-scale model instead of the strongest manually designed baseline3D COVID-19 CT classification · Covid-CTset testaccuracy: 93.87 -> 96.88Helped

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