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Table 3 Feature maps of 3D image blocks based classification results by 3D-ResNet, 3D-MobileNetV2, 3D-DenseNet and 3D-SENet

From: Classifying the tracing difficulty of 3D neuron image blocks based on deep learning

Dataset 3D-ResNet 3D-MobileNetV2 3D-DenseNet 3D-SENet
Accuracy F1 Accuracy F1 Accuracy F1 Accuracy F1
Training 83.50±0.14 85.18±0.13 79.97±0.18 81.89±0.16 \(\underline{84.69\pm 0.16}\) \(\underline{86.33\pm 0.14}\) 82.29±0.05 84.16±0.04
Test \(\underline{81.29\pm 0.39}\) \(\underline{82.78\pm 0.61}\) 78.40±0.23 79.83±0.22 72.03±2.47 75.50±1.29 80.11±0.50 81.63±0.92
  1. Numbers with underline are the best results among all models