Across ten LeNet, VGG, and ResNet models, neuron coverage, k-multisection coverage, boundary coverage, Top-k coverage, and MC/DC show depth- and configuration-dependent trends that are often inconsistent between architectures.
Enriching word vectors with subword information 2017.Transactions of the association for computational linguistics5, 135–146
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Towards Understanding Deep Learning Model in Image Recognition via Coverage Test
Across ten LeNet, VGG, and ResNet models, neuron coverage, k-multisection coverage, boundary coverage, Top-k coverage, and MC/DC show depth- and configuration-dependent trends that are often inconsistent between architectures.