30 KiB
Experimental Results
Models Trained on Various Filters
NOTE: The results in this section contain an oversight in the defense strategy. While models were trained using different filters, they were all defended from FGSM using a Kuwahara filter.
Model Trained on Unfiltered MNIST Dataset
\epsilon |
Accuracy |
|---|---|
| 0.05 | 0.9600 |
| 0.10 | 0.8753 |
| 0.15 | 0.7228 |
| 0.20 | 0.5008 |
| 0.25 | 0.2922 |
| 0.30 | 0.1599 |
Model Trained on Kuwahara (R=5) Filtered MNIST Dataset
\epsilon |
Attacked Accuracy | Filtered Accuracy | Ratio |
|---|---|---|---|
| 0.05 | 0.9605 | 0.9522 | 0.9914 |
| 0.1 | 0.8743 | 0.9031 | 1.0329 |
| 0.15 | 0.7107 | 0.8138 | 1.1451 |
| 0.2 | 0.4876 | 0.6921 | 1.4194 |
| 0.25 | 0.2714 | 0.5350 | 1.9713 |
| 0.3 | 0.1418 | 0.3605 | 2.5423 |
Model Trained on Gaussian Blurred (K-Size=5x5) MNIST Dataset
\epsilon |
Attacked Accuracy | Filtered Accuracy | Ratio |
|---|---|---|---|
| 0.05 | 0.9192 | 0.9325 | 1.014 |
| 0.10 | 0.7629 | 0.8802 | 1.154 |
| 0.15 | 0.4871 | 0.7865 | 1.615 |
| 0.20 | 0.2435 | 0.6556 | 2.692 |
| 0.25 | 0.1093 | 0.5024 | 4.596 |
| 0.30 | 0.0544 | 0.3522 | 6.474 |
Model Trained on Bilateral Filtered (d=5) MNIST Dataset
\epsilon |
Attacked Accuracy | Filtered Accuracy | Ratio |
|---|---|---|---|
| 0.05 | 0.9078 | 0.9287 | 1.023 |
| 0.10 | 0.7303 | 0.8611 | 1.179 |
| 0.15 | 0.4221 | 0.7501 | 1.777 |
| 0.20 | 0.1927 | 0.6007 | 3.117 |
| 0.25 | 0.0873 | 0.4433 | 5.078 |
| 0.30 | 0.0525 | 0.3023 | 5.758 |
Models Defended with Various Filters
Tabulated Results
\epsilon |
Unfiltered | Kuwahara | Bilateral | Gaussian Blur | Random Noise | Snapped Color | 1-Bit | Plurality |
|---|---|---|---|---|---|---|---|---|
| 0.00 | 0.992 | 0.9066 | 0.9391 | 0.9682 | 0.9911 | 0.9913 | 0.9722 | 0.9889 |
| 0.05 | 0.9600 | 0.8700 | 0.8902 | 0.9271 | 0.9603 | 0.9781 | 0.8409 | 0.9600 |
| 0.10 | 0.8753 | 0.8123 | 0.8133 | 0.8516 | 0.8677 | 0.8818 | 0.7919 | 0.8799 |
| 0.15 | 0.7229 | 0.7328 | 0.7098 | 0.7415 | 0.7153 | 0.8408 | 0.7329 | 0.7879 |
| 0.20 | 0.5008 | 0.6301 | 0.5683 | 0.5983 | 0.4941 | 0.7496 | 0.6794 | 0.6467 |
| 0.25 | 0.2922 | 0.5197 | 0.4381 | 0.4591 | 0.2843 | 0.4301 | 0.6233 | 0.4721 |
| 0.30 | 0.1599 | 0.3981 | 0.3364 | 0.3481 | 0.1584 | 0.2091 | 0.5462 | 0.3312 |
Plotted Results
Raw Program Output
====== EPSILON: 0.0 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9920 / 10000 = 0.992
Kuwahara Filter Accuracy = 9066 / 10000 = 0.9066
Bilateral Filter Accuracy = 9391 / 10000 = 0.9391
Gaussian Blur Accuracy = 9682 / 10000 = 0.9682
Random Noise Accuracy = 9911 / 10000 = 0.9911
Snapped Color Accuracy = 9913 / 10000 = 0.9913
1 Bit Accuracy = 9722 / 10000 = 0.9722
Plurality Vote Accuracy = 9889 / 10000 = 0.9889
====== EPSILON: 0.025 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9796 / 10000 = 0.9796
Kuwahara Filter Accuracy = 8909 / 10000 = 0.8909
Bilateral Filter Accuracy = 9184 / 10000 = 0.9184
Gaussian Blur Accuracy = 9512 / 10000 = 0.9512
Random Noise Accuracy = 9786 / 10000 = 0.9786
Snapped Color Accuracy = 9823 / 10000 = 0.9823
1 Bit Accuracy = 8644 / 10000 = 0.8644
Plurality Vote Accuracy = 9746 / 10000 = 0.9746
====== EPSILON: 0.05 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9600 / 10000 = 0.96
Kuwahara Filter Accuracy = 8700 / 10000 = 0.87
Bilateral Filter Accuracy = 8902 / 10000 = 0.8902
Gaussian Blur Accuracy = 9271 / 10000 = 0.9271
Random Noise Accuracy = 9587 / 10000 = 0.9587
Snapped Color Accuracy = 9781 / 10000 = 0.9781
1 Bit Accuracy = 8409 / 10000 = 0.8409
Plurality Vote Accuracy = 9602 / 10000 = 0.9602
====== EPSILON: 0.07500000000000001 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9260 / 10000 = 0.926
Kuwahara Filter Accuracy = 8447 / 10000 = 0.8447
Bilateral Filter Accuracy = 8533 / 10000 = 0.8533
Gaussian Blur Accuracy = 8939 / 10000 = 0.8939
Random Noise Accuracy = 9221 / 10000 = 0.9221
Snapped Color Accuracy = 9228 / 10000 = 0.9228
1 Bit Accuracy = 8174 / 10000 = 0.8174
Plurality Vote Accuracy = 9235 / 10000 = 0.9235
====== EPSILON: 0.1 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 8753 / 10000 = 0.8753
Kuwahara Filter Accuracy = 8123 / 10000 = 0.8123
Bilateral Filter Accuracy = 8133 / 10000 = 0.8133
Gaussian Blur Accuracy = 8516 / 10000 = 0.8516
Random Noise Accuracy = 8702 / 10000 = 0.8702
Snapped Color Accuracy = 8818 / 10000 = 0.8818
1 Bit Accuracy = 7919 / 10000 = 0.7919
Plurality Vote Accuracy = 8802 / 10000 = 0.8802
====== EPSILON: 0.125 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 8104 / 10000 = 0.8104
Kuwahara Filter Accuracy = 7751 / 10000 = 0.7751
Bilateral Filter Accuracy = 7656 / 10000 = 0.7656
Gaussian Blur Accuracy = 7989 / 10000 = 0.7989
Random Noise Accuracy = 8022 / 10000 = 0.8022
Snapped Color Accuracy = 8621 / 10000 = 0.8621
1 Bit Accuracy = 7646 / 10000 = 0.7646
Plurality Vote Accuracy = 8396 / 10000 = 0.8396
====== EPSILON: 0.15000000000000002 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 7229 / 10000 = 0.7229
Kuwahara Filter Accuracy = 7328 / 10000 = 0.7328
Bilateral Filter Accuracy = 7098 / 10000 = 0.7098
Gaussian Blur Accuracy = 7415 / 10000 = 0.7415
Random Noise Accuracy = 7129 / 10000 = 0.7129
Snapped Color Accuracy = 8408 / 10000 = 0.8408
1 Bit Accuracy = 7329 / 10000 = 0.7329
Plurality Vote Accuracy = 7879 / 10000 = 0.7879
====== EPSILON: 0.17500000000000002 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 6207 / 10000 = 0.6207
Kuwahara Filter Accuracy = 6816 / 10000 = 0.6816
Bilateral Filter Accuracy = 6410 / 10000 = 0.641
Gaussian Blur Accuracy = 6741 / 10000 = 0.6741
Random Noise Accuracy = 6096 / 10000 = 0.6096
Snapped Color Accuracy = 7794 / 10000 = 0.7794
1 Bit Accuracy = 7085 / 10000 = 0.7085
Plurality Vote Accuracy = 7176 / 10000 = 0.7176
====== EPSILON: 0.2 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 5008 / 10000 = 0.5008
Kuwahara Filter Accuracy = 6301 / 10000 = 0.6301
Bilateral Filter Accuracy = 5683 / 10000 = 0.5683
Gaussian Blur Accuracy = 5983 / 10000 = 0.5983
Random Noise Accuracy = 4927 / 10000 = 0.4927
Snapped Color Accuracy = 7496 / 10000 = 0.7496
1 Bit Accuracy = 6794 / 10000 = 0.6794
Plurality Vote Accuracy = 6459 / 10000 = 0.6459
====== EPSILON: 0.225 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 3894 / 10000 = 0.3894
Kuwahara Filter Accuracy = 5773 / 10000 = 0.5773
Bilateral Filter Accuracy = 5003 / 10000 = 0.5003
Gaussian Blur Accuracy = 5243 / 10000 = 0.5243
Random Noise Accuracy = 3828 / 10000 = 0.3828
Snapped Color Accuracy = 5289 / 10000 = 0.5289
1 Bit Accuracy = 6512 / 10000 = 0.6512
Plurality Vote Accuracy = 5421 / 10000 = 0.5421
====== EPSILON: 0.25 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 2922 / 10000 = 0.2922
Kuwahara Filter Accuracy = 5197 / 10000 = 0.5197
Bilateral Filter Accuracy = 4381 / 10000 = 0.4381
Gaussian Blur Accuracy = 4591 / 10000 = 0.4591
Random Noise Accuracy = 2855 / 10000 = 0.2855
Snapped Color Accuracy = 4301 / 10000 = 0.4301
1 Bit Accuracy = 6233 / 10000 = 0.6233
Plurality Vote Accuracy = 4716 / 10000 = 0.4716
====== EPSILON: 0.275 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 2149 / 10000 = 0.2149
Kuwahara Filter Accuracy = 4594 / 10000 = 0.4594
Bilateral Filter Accuracy = 3836 / 10000 = 0.3836
Gaussian Blur Accuracy = 3998 / 10000 = 0.3998
Random Noise Accuracy = 2101 / 10000 = 0.2101
Snapped Color Accuracy = 3992 / 10000 = 0.3992
1 Bit Accuracy = 5842 / 10000 = 0.5842
Plurality Vote Accuracy = 4110 / 10000 = 0.411
====== EPSILON: 0.30000000000000004 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 1599 / 10000 = 0.1599
Kuwahara Filter Accuracy = 3981 / 10000 = 0.3981
Bilateral Filter Accuracy = 3364 / 10000 = 0.3364
Gaussian Blur Accuracy = 3481 / 10000 = 0.3481
Random Noise Accuracy = 1544 / 10000 = 0.1544
Snapped Color Accuracy = 2091 / 10000 = 0.2091
1 Bit Accuracy = 5462 / 10000 = 0.5462
Plurality Vote Accuracy = 3287 / 10000 = 0.3287
Gaussian Kuwahara Filter with Varying Radius
Raw Program Output
====== EPSILON: 0.0 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9920 / 10000 = 0.992
Gaussian Kuwahara (strength = 1) = 9897 / 10000 = 0.9897
Gaussian Kuwahara (strength = 3) = 9766 / 10000 = 0.9766
Gaussian Kuwahara (strength = 5) = 9066 / 10000 = 0.9066
Gaussian Kuwahara (strength = 7) = 7355 / 10000 = 0.7355
Gaussian Kuwahara (strength = 9) = 5131 / 10000 = 0.5131
====== EPSILON: 0.025 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9796 / 10000 = 0.9796
Gaussian Kuwahara (strength = 1) = 9808 / 10000 = 0.9808
Gaussian Kuwahara (strength = 3) = 9667 / 10000 = 0.9667
Gaussian Kuwahara (strength = 5) = 8909 / 10000 = 0.8909
Gaussian Kuwahara (strength = 7) = 7035 / 10000 = 0.7035
Gaussian Kuwahara (strength = 9) = 4824 / 10000 = 0.4824
====== EPSILON: 0.05 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9600 / 10000 = 0.96
Gaussian Kuwahara (strength = 1) = 9651 / 10000 = 0.9651
Gaussian Kuwahara (strength = 3) = 9547 / 10000 = 0.9547
Gaussian Kuwahara (strength = 5) = 8700 / 10000 = 0.87
Gaussian Kuwahara (strength = 7) = 6713 / 10000 = 0.6713
Gaussian Kuwahara (strength = 9) = 4538 / 10000 = 0.4538
====== EPSILON: 0.07500000000000001 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9260 / 10000 = 0.926
Gaussian Kuwahara (strength = 1) = 9412 / 10000 = 0.9412
Gaussian Kuwahara (strength = 3) = 9334 / 10000 = 0.9334
Gaussian Kuwahara (strength = 5) = 8447 / 10000 = 0.8447
Gaussian Kuwahara (strength = 7) = 6354 / 10000 = 0.6354
Gaussian Kuwahara (strength = 9) = 4260 / 10000 = 0.426
====== EPSILON: 0.1 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 8753 / 10000 = 0.8753
Gaussian Kuwahara (strength = 1) = 9035 / 10000 = 0.9035
Gaussian Kuwahara (strength = 3) = 9107 / 10000 = 0.9107
Gaussian Kuwahara (strength = 5) = 8123 / 10000 = 0.8123
Gaussian Kuwahara (strength = 7) = 5970 / 10000 = 0.597
Gaussian Kuwahara (strength = 9) = 3915 / 10000 = 0.3915
====== EPSILON: 0.125 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 8104 / 10000 = 0.8104
Gaussian Kuwahara (strength = 1) = 8539 / 10000 = 0.8539
Gaussian Kuwahara (strength = 3) = 8785 / 10000 = 0.8785
Gaussian Kuwahara (strength = 5) = 7751 / 10000 = 0.7751
Gaussian Kuwahara (strength = 7) = 5616 / 10000 = 0.5616
Gaussian Kuwahara (strength = 9) = 3620 / 10000 = 0.362
====== EPSILON: 0.15000000000000002 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 7229 / 10000 = 0.7229
Gaussian Kuwahara (strength = 1) = 7925 / 10000 = 0.7925
Gaussian Kuwahara (strength = 3) = 8328 / 10000 = 0.8328
Gaussian Kuwahara (strength = 5) = 7328 / 10000 = 0.7328
Gaussian Kuwahara (strength = 7) = 5236 / 10000 = 0.5236
Gaussian Kuwahara (strength = 9) = 3344 / 10000 = 0.3344
====== EPSILON: 0.17500000000000002 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 6207 / 10000 = 0.6207
Gaussian Kuwahara (strength = 1) = 7078 / 10000 = 0.7078
Gaussian Kuwahara (strength = 3) = 7808 / 10000 = 0.7808
Gaussian Kuwahara (strength = 5) = 6816 / 10000 = 0.6816
Gaussian Kuwahara (strength = 7) = 4868 / 10000 = 0.4868
Gaussian Kuwahara (strength = 9) = 3090 / 10000 = 0.309
====== EPSILON: 0.2 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 5008 / 10000 = 0.5008
Gaussian Kuwahara (strength = 1) = 6125 / 10000 = 0.6125
Gaussian Kuwahara (strength = 3) = 7179 / 10000 = 0.7179
Gaussian Kuwahara (strength = 5) = 6301 / 10000 = 0.6301
Gaussian Kuwahara (strength = 7) = 4513 / 10000 = 0.4513
Gaussian Kuwahara (strength = 9) = 2865 / 10000 = 0.2865
====== EPSILON: 0.225 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 3894 / 10000 = 0.3894
Gaussian Kuwahara (strength = 1) = 4979 / 10000 = 0.4979
Gaussian Kuwahara (strength = 3) = 6460 / 10000 = 0.646
Gaussian Kuwahara (strength = 5) = 5773 / 10000 = 0.5773
Gaussian Kuwahara (strength = 7) = 4242 / 10000 = 0.4242
Gaussian Kuwahara (strength = 9) = 2702 / 10000 = 0.2702
====== EPSILON: 0.25 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 2922 / 10000 = 0.2922
Gaussian Kuwahara (strength = 1) = 3927 / 10000 = 0.3927
Gaussian Kuwahara (strength = 3) = 5640 / 10000 = 0.564
Gaussian Kuwahara (strength = 5) = 5197 / 10000 = 0.5197
Gaussian Kuwahara (strength = 7) = 3859 / 10000 = 0.3859
Gaussian Kuwahara (strength = 9) = 2493 / 10000 = 0.2493
====== EPSILON: 0.275 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 2149 / 10000 = 0.2149
Gaussian Kuwahara (strength = 1) = 3023 / 10000 = 0.3023
Gaussian Kuwahara (strength = 3) = 4761 / 10000 = 0.4761
Gaussian Kuwahara (strength = 5) = 4594 / 10000 = 0.4594
Gaussian Kuwahara (strength = 7) = 3494 / 10000 = 0.3494
Gaussian Kuwahara (strength = 9) = 2354 / 10000 = 0.2354
====== EPSILON: 0.30000000000000004 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 1599 / 10000 = 0.1599
Gaussian Kuwahara (strength = 1) = 2289 / 10000 = 0.2289
Gaussian Kuwahara (strength = 3) = 3839 / 10000 = 0.3839
Gaussian Kuwahara (strength = 5) = 3981 / 10000 = 0.3981
Gaussian Kuwahara (strength = 7) = 3182 / 10000 = 0.3182
Gaussian Kuwahara (strength = 9) = 2232 / 10000 = 0.2232
Mean Kuwahara with Varying Radius
Raw Program Output
====== EPSILON: 0.0 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9920 / 10000 = 0.992
Mean Kuwahara (strength = 1) = 9880 / 10000 = 0.988
Mean Kuwahara (strength = 3) = 7536 / 10000 = 0.7536
Mean Kuwahara (strength = 5) = 3667 / 10000 = 0.3667
Mean Kuwahara (strength = 7) = 1763 / 10000 = 0.1763
Mean Kuwahara (strength = 9) = 1339 / 10000 = 0.1339
====== EPSILON: 0.025 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9796 / 10000 = 0.9796
Mean Kuwahara (strength = 1) = 9795 / 10000 = 0.9795
Mean Kuwahara (strength = 3) = 7359 / 10000 = 0.7359
Mean Kuwahara (strength = 5) = 3496 / 10000 = 0.3496
Mean Kuwahara (strength = 7) = 1710 / 10000 = 0.171
Mean Kuwahara (strength = 9) = 1318 / 10000 = 0.1318
====== EPSILON: 0.05 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9600 / 10000 = 0.96
Mean Kuwahara (strength = 1) = 9650 / 10000 = 0.965
Mean Kuwahara (strength = 3) = 7129 / 10000 = 0.7129
Mean Kuwahara (strength = 5) = 3295 / 10000 = 0.3295
Mean Kuwahara (strength = 7) = 1637 / 10000 = 0.1637
Mean Kuwahara (strength = 9) = 1286 / 10000 = 0.1286
====== EPSILON: 0.07500000000000001 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9260 / 10000 = 0.926
Mean Kuwahara (strength = 1) = 9460 / 10000 = 0.946
Mean Kuwahara (strength = 3) = 6871 / 10000 = 0.6871
Mean Kuwahara (strength = 5) = 3119 / 10000 = 0.3119
Mean Kuwahara (strength = 7) = 1578 / 10000 = 0.1578
Mean Kuwahara (strength = 9) = 1244 / 10000 = 0.1244
====== EPSILON: 0.1 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 8753 / 10000 = 0.8753
Mean Kuwahara (strength = 1) = 9160 / 10000 = 0.916
Mean Kuwahara (strength = 3) = 6617 / 10000 = 0.6617
Mean Kuwahara (strength = 5) = 2841 / 10000 = 0.2841
Mean Kuwahara (strength = 7) = 1497 / 10000 = 0.1497
Mean Kuwahara (strength = 9) = 1228 / 10000 = 0.1228
====== EPSILON: 0.125 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 8104 / 10000 = 0.8104
Mean Kuwahara (strength = 1) = 8746 / 10000 = 0.8746
Mean Kuwahara (strength = 3) = 6317 / 10000 = 0.6317
Mean Kuwahara (strength = 5) = 2587 / 10000 = 0.2587
Mean Kuwahara (strength = 7) = 1422 / 10000 = 0.1422
Mean Kuwahara (strength = 9) = 1211 / 10000 = 0.1211
====== EPSILON: 0.15000000000000002 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 7229 / 10000 = 0.7229
Mean Kuwahara (strength = 1) = 8235 / 10000 = 0.8235
Mean Kuwahara (strength = 3) = 6019 / 10000 = 0.6019
Mean Kuwahara (strength = 5) = 2395 / 10000 = 0.2395
Mean Kuwahara (strength = 7) = 1360 / 10000 = 0.136
Mean Kuwahara (strength = 9) = 1193 / 10000 = 0.1193
====== EPSILON: 0.17500000000000002 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 6207 / 10000 = 0.6207
Mean Kuwahara (strength = 1) = 7499 / 10000 = 0.7499
Mean Kuwahara (strength = 3) = 5699 / 10000 = 0.5699
Mean Kuwahara (strength = 5) = 2253 / 10000 = 0.2253
Mean Kuwahara (strength = 7) = 1340 / 10000 = 0.134
Mean Kuwahara (strength = 9) = 1164 / 10000 = 0.1164
====== EPSILON: 0.2 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 5008 / 10000 = 0.5008
Mean Kuwahara (strength = 1) = 6650 / 10000 = 0.665
Mean Kuwahara (strength = 3) = 5420 / 10000 = 0.542
Mean Kuwahara (strength = 5) = 2168 / 10000 = 0.2168
Mean Kuwahara (strength = 7) = 1335 / 10000 = 0.1335
Mean Kuwahara (strength = 9) = 1138 / 10000 = 0.1138
====== EPSILON: 0.225 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 3894 / 10000 = 0.3894
Mean Kuwahara (strength = 1) = 5642 / 10000 = 0.5642
Mean Kuwahara (strength = 3) = 5087 / 10000 = 0.5087
Mean Kuwahara (strength = 5) = 2064 / 10000 = 0.2064
Mean Kuwahara (strength = 7) = 1328 / 10000 = 0.1328
Mean Kuwahara (strength = 9) = 1129 / 10000 = 0.1129
====== EPSILON: 0.25 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 2922 / 10000 = 0.2922
Mean Kuwahara (strength = 1) = 4739 / 10000 = 0.4739
Mean Kuwahara (strength = 3) = 4773 / 10000 = 0.4773
Mean Kuwahara (strength = 5) = 1993 / 10000 = 0.1993
Mean Kuwahara (strength = 7) = 1306 / 10000 = 0.1306
Mean Kuwahara (strength = 9) = 1145 / 10000 = 0.1145
====== EPSILON: 0.275 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 2149 / 10000 = 0.2149
Mean Kuwahara (strength = 1) = 3638 / 10000 = 0.3638
Mean Kuwahara (strength = 3) = 4370 / 10000 = 0.437
Mean Kuwahara (strength = 5) = 1921 / 10000 = 0.1921
Mean Kuwahara (strength = 7) = 1309 / 10000 = 0.1309
Mean Kuwahara (strength = 9) = 1159 / 10000 = 0.1159
====== EPSILON: 0.30000000000000004 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 1599 / 10000 = 0.1599
Mean Kuwahara (strength = 1) = 2659 / 10000 = 0.2659
Mean Kuwahara (strength = 3) = 3912 / 10000 = 0.3912
Mean Kuwahara (strength = 5) = 1854 / 10000 = 0.1854
Mean Kuwahara (strength = 7) = 1307 / 10000 = 0.1307
Mean Kuwahara (strength = 9) = 1166 / 10000 = 0.1166
Bilateral Filter (Sigma = 50)
Raw Program Output
====== EPSILON: 0.0 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9920 / 10000 = 0.992
Bilateral Filter (strength = 1) = 9887 / 10000 = 0.9887
Bilateral Filter (strength = 3) = 9887 / 10000 = 0.9887
Bilateral Filter (strength = 5) = 9391 / 10000 = 0.9391
Bilateral Filter (strength = 7) = 5584 / 10000 = 0.5584
Bilateral Filter (strength = 9) = 2568 / 10000 = 0.2568
====== EPSILON: 0.025 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9796 / 10000 = 0.9796
Bilateral Filter (strength = 1) = 9809 / 10000 = 0.9809
Bilateral Filter (strength = 3) = 9809 / 10000 = 0.9809
Bilateral Filter (strength = 5) = 9184 / 10000 = 0.9184
Bilateral Filter (strength = 7) = 5198 / 10000 = 0.5198
Bilateral Filter (strength = 9) = 2410 / 10000 = 0.241
====== EPSILON: 0.05 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9600 / 10000 = 0.96
Bilateral Filter (strength = 1) = 9695 / 10000 = 0.9695
Bilateral Filter (strength = 3) = 9695 / 10000 = 0.9695
Bilateral Filter (strength = 5) = 8902 / 10000 = 0.8902
Bilateral Filter (strength = 7) = 4831 / 10000 = 0.4831
Bilateral Filter (strength = 9) = 2245 / 10000 = 0.2245
====== EPSILON: 0.07500000000000001 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9260 / 10000 = 0.926
Bilateral Filter (strength = 1) = 9482 / 10000 = 0.9482
Bilateral Filter (strength = 3) = 9482 / 10000 = 0.9482
Bilateral Filter (strength = 5) = 8533 / 10000 = 0.8533
Bilateral Filter (strength = 7) = 4436 / 10000 = 0.4436
Bilateral Filter (strength = 9) = 2079 / 10000 = 0.2079
====== EPSILON: 0.1 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 8753 / 10000 = 0.8753
Bilateral Filter (strength = 1) = 9142 / 10000 = 0.9142
Bilateral Filter (strength = 3) = 9142 / 10000 = 0.9142
Bilateral Filter (strength = 5) = 8133 / 10000 = 0.8133
Bilateral Filter (strength = 7) = 4019 / 10000 = 0.4019
Bilateral Filter (strength = 9) = 1915 / 10000 = 0.1915
====== EPSILON: 0.125 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 8104 / 10000 = 0.8104
Bilateral Filter (strength = 1) = 8714 / 10000 = 0.8714
Bilateral Filter (strength = 3) = 8714 / 10000 = 0.8714
Bilateral Filter (strength = 5) = 7656 / 10000 = 0.7656
Bilateral Filter (strength = 7) = 3641 / 10000 = 0.3641
Bilateral Filter (strength = 9) = 1792 / 10000 = 0.1792
====== EPSILON: 0.15000000000000002 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 7229 / 10000 = 0.7229
Bilateral Filter (strength = 1) = 8169 / 10000 = 0.8169
Bilateral Filter (strength = 3) = 8169 / 10000 = 0.8169
Bilateral Filter (strength = 5) = 7098 / 10000 = 0.7098
Bilateral Filter (strength = 7) = 3299 / 10000 = 0.3299
Bilateral Filter (strength = 9) = 1681 / 10000 = 0.1681
====== EPSILON: 0.17500000000000002 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 6207 / 10000 = 0.6207
Bilateral Filter (strength = 1) = 7477 / 10000 = 0.7477
Bilateral Filter (strength = 3) = 7477 / 10000 = 0.7477
Bilateral Filter (strength = 5) = 6410 / 10000 = 0.641
Bilateral Filter (strength = 7) = 2978 / 10000 = 0.2978
Bilateral Filter (strength = 9) = 1610 / 10000 = 0.161
====== EPSILON: 0.2 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 5008 / 10000 = 0.5008
Bilateral Filter (strength = 1) = 6619 / 10000 = 0.6619
Bilateral Filter (strength = 3) = 6619 / 10000 = 0.6619
Bilateral Filter (strength = 5) = 5683 / 10000 = 0.5683
Bilateral Filter (strength = 7) = 2723 / 10000 = 0.2723
Bilateral Filter (strength = 9) = 1563 / 10000 = 0.1563
====== EPSILON: 0.225 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 3894 / 10000 = 0.3894
Bilateral Filter (strength = 1) = 5767 / 10000 = 0.5767
Bilateral Filter (strength = 3) = 5767 / 10000 = 0.5767
Bilateral Filter (strength = 5) = 5003 / 10000 = 0.5003
Bilateral Filter (strength = 7) = 2476 / 10000 = 0.2476
Bilateral Filter (strength = 9) = 1517 / 10000 = 0.1517
====== EPSILON: 0.25 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 2922 / 10000 = 0.2922
Bilateral Filter (strength = 1) = 4922 / 10000 = 0.4922
Bilateral Filter (strength = 3) = 4922 / 10000 = 0.4922
Bilateral Filter (strength = 5) = 4381 / 10000 = 0.4381
Bilateral Filter (strength = 7) = 2288 / 10000 = 0.2288
Bilateral Filter (strength = 9) = 1484 / 10000 = 0.1484
====== EPSILON: 0.275 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 2149 / 10000 = 0.2149
Bilateral Filter (strength = 1) = 4133 / 10000 = 0.4133
Bilateral Filter (strength = 3) = 4133 / 10000 = 0.4133
Bilateral Filter (strength = 5) = 3836 / 10000 = 0.3836
Bilateral Filter (strength = 7) = 2126 / 10000 = 0.2126
Bilateral Filter (strength = 9) = 1460 / 10000 = 0.146
====== EPSILON: 0.30000000000000004 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 1599 / 10000 = 0.1599
Bilateral Filter (strength = 1) = 3468 / 10000 = 0.3468
Bilateral Filter (strength = 3) = 3468 / 10000 = 0.3468
Bilateral Filter (strength = 5) = 3364 / 10000 = 0.3364
Bilateral Filter (strength = 7) = 1999 / 10000 = 0.1999
Bilateral Filter (strength = 9) = 1444 / 10000 = 0.1444
Gaussian Blur
====== EPSILON: 0.0 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9920 / 10000 = 0.992
Gaussian Blur (strength = 1) = 9920 / 10000 = 0.992
Gaussian Blur (strength = 3) = 9879 / 10000 = 0.9879
Gaussian Blur (strength = 5) = 9682 / 10000 = 0.9682
Gaussian Blur (strength = 7) = 7731 / 10000 = 0.7731
Gaussian Blur (strength = 9) = 5250 / 10000 = 0.525
====== EPSILON: 0.025 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9796 / 10000 = 0.9796
Gaussian Blur (strength = 1) = 9796 / 10000 = 0.9796
Gaussian Blur (strength = 3) = 9801 / 10000 = 0.9801
Gaussian Blur (strength = 5) = 9512 / 10000 = 0.9512
Gaussian Blur (strength = 7) = 7381 / 10000 = 0.7381
Gaussian Blur (strength = 9) = 4862 / 10000 = 0.4862
====== EPSILON: 0.05 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9600 / 10000 = 0.96
Gaussian Blur (strength = 1) = 9600 / 10000 = 0.96
Gaussian Blur (strength = 3) = 9674 / 10000 = 0.9674
Gaussian Blur (strength = 5) = 9271 / 10000 = 0.9271
Gaussian Blur (strength = 7) = 6922 / 10000 = 0.6922
Gaussian Blur (strength = 9) = 4446 / 10000 = 0.4446
====== EPSILON: 0.07500000000000001 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 9260 / 10000 = 0.926
Gaussian Blur (strength = 1) = 9260 / 10000 = 0.926
Gaussian Blur (strength = 3) = 9460 / 10000 = 0.946
Gaussian Blur (strength = 5) = 8939 / 10000 = 0.8939
Gaussian Blur (strength = 7) = 6427 / 10000 = 0.6427
Gaussian Blur (strength = 9) = 3989 / 10000 = 0.3989
====== EPSILON: 0.1 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 8753 / 10000 = 0.8753
Gaussian Blur (strength = 1) = 8753 / 10000 = 0.8753
Gaussian Blur (strength = 3) = 9133 / 10000 = 0.9133
Gaussian Blur (strength = 5) = 8516 / 10000 = 0.8516
Gaussian Blur (strength = 7) = 5881 / 10000 = 0.5881
Gaussian Blur (strength = 9) = 3603 / 10000 = 0.3603
====== EPSILON: 0.125 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 8104 / 10000 = 0.8104
Gaussian Blur (strength = 1) = 8104 / 10000 = 0.8104
Gaussian Blur (strength = 3) = 8690 / 10000 = 0.869
Gaussian Blur (strength = 5) = 7989 / 10000 = 0.7989
Gaussian Blur (strength = 7) = 5278 / 10000 = 0.5278
Gaussian Blur (strength = 9) = 3263 / 10000 = 0.3263
====== EPSILON: 0.15000000000000002 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 7229 / 10000 = 0.7229
Gaussian Blur (strength = 1) = 7229 / 10000 = 0.7229
Gaussian Blur (strength = 3) = 8135 / 10000 = 0.8135
Gaussian Blur (strength = 5) = 7415 / 10000 = 0.7415
Gaussian Blur (strength = 7) = 4710 / 10000 = 0.471
Gaussian Blur (strength = 9) = 2968 / 10000 = 0.2968
====== EPSILON: 0.17500000000000002 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 6207 / 10000 = 0.6207
Gaussian Blur (strength = 1) = 6207 / 10000 = 0.6207
Gaussian Blur (strength = 3) = 7456 / 10000 = 0.7456
Gaussian Blur (strength = 5) = 6741 / 10000 = 0.6741
Gaussian Blur (strength = 7) = 4224 / 10000 = 0.4224
Gaussian Blur (strength = 9) = 2683 / 10000 = 0.2683
====== EPSILON: 0.2 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 5008 / 10000 = 0.5008
Gaussian Blur (strength = 1) = 5008 / 10000 = 0.5008
Gaussian Blur (strength = 3) = 6636 / 10000 = 0.6636
Gaussian Blur (strength = 5) = 5983 / 10000 = 0.5983
Gaussian Blur (strength = 7) = 3755 / 10000 = 0.3755
Gaussian Blur (strength = 9) = 2453 / 10000 = 0.2453
====== EPSILON: 0.225 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 3894 / 10000 = 0.3894
Gaussian Blur (strength = 1) = 3894 / 10000 = 0.3894
Gaussian Blur (strength = 3) = 5821 / 10000 = 0.5821
Gaussian Blur (strength = 5) = 5243 / 10000 = 0.5243
Gaussian Blur (strength = 7) = 3359 / 10000 = 0.3359
Gaussian Blur (strength = 9) = 2269 / 10000 = 0.2269
====== EPSILON: 0.25 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 2922 / 10000 = 0.2922
Gaussian Blur (strength = 1) = 2922 / 10000 = 0.2922
Gaussian Blur (strength = 3) = 5050 / 10000 = 0.505
Gaussian Blur (strength = 5) = 4591 / 10000 = 0.4591
Gaussian Blur (strength = 7) = 3034 / 10000 = 0.3034
Gaussian Blur (strength = 9) = 2112 / 10000 = 0.2112
====== EPSILON: 0.275 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 2149 / 10000 = 0.2149
Gaussian Blur (strength = 1) = 2149 / 10000 = 0.2149
Gaussian Blur (strength = 3) = 4290 / 10000 = 0.429
Gaussian Blur (strength = 5) = 3998 / 10000 = 0.3998
Gaussian Blur (strength = 7) = 2743 / 10000 = 0.2743
Gaussian Blur (strength = 9) = 1983 / 10000 = 0.1983
====== EPSILON: 0.30000000000000004 ======
Clean (No Filter) Accuracy = 9920 / 10000 = 0.992
Unfiltered Accuracy = 1599 / 10000 = 0.1599
Gaussian Blur (strength = 1) = 1599 / 10000 = 0.1599
Gaussian Blur (strength = 3) = 3648 / 10000 = 0.3648
Gaussian Blur (strength = 5) = 3481 / 10000 = 0.3481
Gaussian Blur (strength = 7) = 2493 / 10000 = 0.2493
Gaussian Blur (strength = 9) = 1884 / 10000 = 0.1884