# 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 ![Results Plot](../Plurality_Vote_Accuracy_Agaisnt_Individual_Filters.png) ### 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