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Table 2 Final results of the experiment of selecting the optimal deep neural network architecture and the values of the training process parameters (test phase)

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

No.

DNN

wIoU

gAcc

mAcc

mIoU

mBFS

Avg

Min

Max

Std

1

DeepLab-v3-ResNet-18 (15)

0.897

0.93

0.79

0.97

0.03

0.74

0.62

0.80

2

DeepLab-v3-ResNet-50 (7)

0.891

0.93

0.74

0.97

0.03

0.75

0.63

0.79

3

DeepLab-v3-Inception-... (10)

0.891

0.93

0.72

0.97

0.04

0.72

0.54

0.79

.

.

.

.

.

.

.

.

.

.

7

DeepLab-v3-Xception (8)

0.883

0.92

0.74

0.97

0.04

0.73

0.56

0.77

.

.

.

.

.

.

.

.

.

.

56

fcnLayers (8)

0.825

0.88

0.66

0.96

0.05

0.64

0.52

0.61

57

SegNetLayers (4)

0.825

0.88

0, 65

0.96

0.06

0.49

0.36

0.66

.

.

.

.

.

.

.

.

.

.

71

SegNetLayers (7)

0.749

0.82

0.58

0.95

0.08

0.32

0.22

0.50