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Table 2 Comparison of different CNN and RNN pair

From: A multi-label classification model for full slice brain computerised tomography image

Model Parameters Precision Recall F1
ResNet50-GRU 10,106,889 63.56% 47.11% 0.5411
ResNet50-LSTM 13,253,641 57.35% 49.16% 0.5259
VGG16-GRU 5,382,153 67.57% 61.04% 0.6412
VGG16-LSTM 6,956,041 58.13% 57.87% 0.5794
VGG19-GRU 5,382,153 58.61% 57.49% 0.5802
VGG19-LSTM 6,956,041 46.89% 65.45% 0.5462
DenseNet121-GRU 6,957,065 60.93% 45.24% 0.5168
DenseNet121-LSTM 9,055,241 48.59% 47.62% 0.4883