|
Data augmentation \(\downarrow \)
|
ResNet18
|
ResNet34
|
ResNet101
|
|---|
|
IA
|
FIA
|
LA
|
IA
|
FIA
|
LA
|
IA
|
FIA
|
LA
|
|---|
|
Baseline
|
83.19
|
78.41
|
89.56
|
84.85
|
81.65
|
91.36
|
82.49
|
83.09
|
88.12
|
|
RV Flip
|
87.98
|
84.17
|
92.08
|
88.65
|
87.56
|
92.44
|
85.96
|
85.25
|
90.28
|
|
RH Flip
|
87.87
|
84.53
|
92.80
|
88.98
|
87.12
|
91.72
|
84.63
|
81.65
|
90.64
|
|
RV + RH Flip
|
88.43
|
85.97
|
93.88
|
89.20
|
86.69
|
92.80
|
87.80
|
85.97
|
93.52
|
|
RC
|
82.32
|
80.93
|
88.48
|
83.67
|
81.65
|
87.05
|
82.38
|
83.09
|
89.20
|
|
RC + RV Flip
|
83.78
|
83.09
|
87.76
|
86.25
|
84.17
|
93.16
|
83.60
|
82.01
|
88.12
|
|
RC + RH Flip
|
83.12
|
81.64
|
87.76
|
86.10
|
84.53
|
91.72
|
83.71
|
82.37
|
86.69
|
|
RC + RV + RH Flip
|
84.59
|
85.25
|
88.84
|
83.38
|
81.65
|
86.33
|
82.57
|
82.73
|
85.97
|
|
RR
|
87.80
|
87.76
|
91.72
|
89.27
|
88.13
|
94.96
|
88.72
|
89.92
|
92.80
|
- Image Accuracy (IA), First Image Accuracy (FIA) and Leaf Accuracy (LA) are compared to baseline accuracies obtained without data augmentation. The highest accuracy in each column is highlighted in bold. All models here employ the Adam optimizer with learning rate (lr) \(=1e^{-4}\)
- RV Random Vertical, RH Random Horizontal, RC Random Crop, RR Random Rotation
