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TSWC2017
Information
Contact Name: Carl Lemaire
Email: carl.lemaire@usherbrooke.ca
Organization: Université de Sherbrooke
Method's Name: ResNet-50
Reference: K He, X Zhang, S. Ren, J. Sun. Deep Residual Learning for Image Recognition. Proceedings of CVPR 2016, p.770-778.
Project Website:
Evaluation Metrics
Precision of each category :
$$ Pre_i = \frac{TP_i}{TP_i + FP_i}$$
Articulated Truck
Bicycle
Bus
Car
Motorcycle
Non-motorized Vehicle
Pedestrian
Pickup Truck
Single Unit Truck
Work Van
Background
0.8605
0.7467
0.9720
0.9784
0.8773
0.5717
0.9212
0.9107
0.7332
0.8706
0.9977
Recall of each category:
$$ Rec_i = \frac{TP_i}{TP_i + FN_i}$$
Articulated Truck
Bicycle
Bus
Car
Motorcycle
Non-motorized Vehicle
Pedestrian
Pickup Truck
Single Unit Truck
Work Van
Background
0.9374
0.8827
0.9407
0.9788
0.8808
0.6370
0.8812
0.9272
0.7492
0.7696
0.9917
Accuracy: 0.9668
$$ Acc = \frac{TP}{Number of Testing Images}$$
Mean Recall: 0.8706
$$ {mRec} = {\rm mean}({Rec_i})$$
Mean Precision: 0.8582
$$ {mPre} = {\rm mean}({Pre_i})$$
Cohen Kappa Score: 0.9484
Confusion Matrix (%):
Predicted
Articulated Truck
Bicycle
Bus
Car
Motorcycle
Non-motorized Vehicle
Pedestrian
Pickup Truck
Single Unit Truck
Work Van
Background
True
Articulated Truck
93.74
0.00
0.35
0.35
0.00
1.01
0.04
0.35
4.06
0.04
0.08
Bicycle
0.00
88.27
0.18
0.00
2.80
0.18
8.23
0.00
0.00
0.00
0.35
Bus
1.55
0.00
94.07
0.58
0.00
1.28
0.00
0.16
1.24
0.81
0.31
Car
0.05
0.01
0.02
97.88
0.02
0.04
0.01
1.55
0.01
0.33
0.07
Motorcycle
0.00
4.85
0.00
5.45
88.08
0.00
1.21
0.40
0.00
0.00
0.00
Non-motorized Vehicle
11.42
0.23
0.91
6.39
0.68
63.70
1.14
2.74
10.96
0.23
1.60
Pedestrian
0.13
8.50
0.00
1.15
0.83
0.06
88.12
0.06
0.00
0.00
1.15
Pickup Truck
0.20
0.00
0.05
5.67
0.02
0.33
0.01
92.72
0.78
0.19
0.03
Single Unit Truck
13.67
0.00
0.55
2.81
0.78
1.33
0.08
4.45
74.92
1.25
0.16
Work Van
0.62
0.00
0.78
16.52
0.00
0.29
0.04
2.44
2.31
76.96
0.04
Background
0.13
0.02
0.02
0.38
0.01
0.14
0.12
0.01
0.01
0.00
99.17