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Table 3 Comparison of the accuracy of selected deep neural models in the segmentation task

From: Semantic segmentation of human oocyte images using deep neural networks

DNN DeepLab-v3-ResNet-18 (15) DeepLab-v3-ResNet-50 (7) DeepLab-v3-Inception-.
Area name DSC Acc IoU mBFS DSC Acc IoU mBFS DSC Acc IoU mBFS
CPM_CC 0.92 0.96 0.92 0.89 0.85 0.94 0.89 0.86 0.88 0.94 0.91 0.89
CPM_DCG 0.46 0.79 0.75 0.64 0.46 0.70 0.53 0.63 0.29 0.85 0.61 0.64
CPM_CGA 0.35 0.54 0.44 0.27 0.28 0.76 0.55 0.43 0.39 0.85 0.60 0.20
CPM_SERC \( - \) \( - \) \( - \) \( - \) \( - \) \( - \) \( - \) \( - \) 0.10 0.11 0.09 0.56
CPM_VAC 0.16 0.43 0.21 0.96 0.20 0.11 0.11 0.56 0.03 0.08 0.07 0.13
CPM_DC 0.49 0.99 0.75 0.84 0.58 0.95 0.93 0.80 0.49 0.99 0.89 0.85
PB_FPB 0.43 0.55 0.37 0.64 0.56 0.62 0.54 0.67 0.57 0.66 0.54 0.74
PB_MPB \( - \) \( - \) \( - \) \( - \) \( - \) \( - \) \( - \) \( - \) 0.00 \( - \) 0.00 \( - \)
PB_FFPB 0.28 0.43 0.31 0.61 0.27 0.62 0.37 0.67 0.32 0.50 0.40 0.62
PVS 0.79 0.83 0.69 0.93 0.76 0.81 0.70 0.90 0.78 0.86 0.70 0.90
ZP 0.88 0.90 0.82 0.82 0.87 0.92 0.82 0.78 0.84 0.90 0.81 0.76
CCC 0.68 0.86 0.71 0.67 0.70 0.87 0.73 0.65 0.73 0.89 0.75 0.64
GV 0.54 0.70 0.55 0.33 0.46 0.81 0.47 0.53 0.22 0.86 0.33 0.66
Background 0.98 0.98 0.96 0.93 0.98 0.97 0.96 0.92 0.98 0.97 0.96 0.91