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Models/Efficientnet-b0

Efficientnet-b0

Reported on 8 benchmarks across 2 tasks · 1 paper · 6 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Methodology4 results

ClassificationonNCT-CRC-HE-100K
Accuracy (%)· 2019-05-28
95.59
SOTA
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks arXiv:1905.11946
ClassificationonNCT-CRC-HE-100K
F1-Score· 2019-05-28
97.48
SOTA
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks arXiv:1905.11946
ClassificationonNCT-CRC-HE-100K
Specificity· 2019-05-28
99.45
SOTA
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks arXiv:1905.11946
ClassificationonNCT-CRC-HE-100K
Precision· 2019-05-28
99.89
best: 100 (ResNet-50)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks arXiv:1905.11946

Medical4 results

Medical Image ClassificationonNCT-CRC-HE-100K
Accuracy (%)· 2019-05-28
95.59
SOTA
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks arXiv:1905.11946
Medical Image ClassificationonNCT-CRC-HE-100K
F1-Score· 2019-05-28
97.48
SOTA
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks arXiv:1905.11946
Medical Image ClassificationonNCT-CRC-HE-100K
Specificity· 2019-05-28
99.45
SOTA
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks arXiv:1905.11946
Medical Image ClassificationonNCT-CRC-HE-100K
Precision· 2019-05-28
99.89
best: 100 (ResNet-50)
EfficientNet: Rethinking Model Scaling for Convolutional Neural Networks arXiv:1905.11946