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Table 2

F2-score classification performance on the ROAD dataset.

Class Supervised Random init VAE ImageNet ROAD-KNN ROAD
Normal 0.942 ± 0.002 0.940 ± 0.012 0.940 ± 0.004 0.921 ± 0.050 0.940 ± 0.000 0.942 ± 0.006
First order data loss 0.978 ± 0.049 0.975 ± 0.062 0.985 ± 0.031 0.978 ± 0.040 0.988 ± 0.018 0.986 ± 0.039
Second order data loss 0.767 ± 0.090 0.714 ± 0.122 0.763 ± 0.099 0.779 ± 0.13 0.726 ± 0.136 0.789 ± 0.073
High noise element 0.777 ± 0.140 0.583 ± 0.205 0.501 ± 0.243 0.662 ± 0.258 0.719 ± 0.187 0.810 ± 0.162
Oscillating tile 0.837 ± 0.143 0.705 ± 0.198 0.752 ± 0.168 0.731 ± 0.198 0.838 ± 0.140 0.820 ± 0.165
Source in the side-lobes 0.775 ± 0.031 0.781 ± 0.058 0.741 ± 0.099 0.770 ± 0.076 0.788 ± 0.043 0.791 ± 0.037
Galactic plane 0.797 ± 0.078 0.781 ± 0.041 0.773 ± 0.053 0.839 ± 0.053 0.787 ± 0.075 0.819 ± 0.084
Solar storm 0.987 ± 0.016 0.980 ± 0.021 0.991 ± 0.028 0.985 ± 0.017 0.986 ± 0.016 0.987 ± 0.016
Lightning storm 0.948 + 0.040 0.897 ± 0.057 0.918 ± 0.060 0.935 ± 0.053 0.946 ± 0.046 0.948 ± 0.042
Ionospheric RFI reflections 0.998 ± 0.009 1.000 ± 0.000 1.000 ± 0.000 1.000 ± 0.000 0.996 ± 0.012 0.998 ± 0.009

Notes. Bold is the best performance per class and the ResNet34 is used for all relevant backbones.

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