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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