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Analyzing inter-reader variability affecting deep ensemble learning for COVID-19 detection in chest radiographs

Fig 5

The architecture of the CNNs used in the first stage of repeated CXR-specific pretraining.

I/P = Input, I-PCNN = truncated ImageNet-pretrained CNNs, ZP = Zero-padding, CONV = Extra convolution layer, GAP = Global Average Pooling, DO = Dropout, D = Final dense layer with Softmax activation.

Fig 5

doi: https://doi.org/10.1371/journal.pone.0242301.g005