# A Convolutional Neural Network as a Potential Tool for Camouflage Assessment
## 3 Experiment 2: YOLO vs. Human Camouflaged Person Detection on Photosimulations
### Results
(**a**) Mean detection probability (i.e., the confidence score generated by YOLO) when the person was wearing a uniform in an average color derived from a bush/desert ROI. The panels on the left indicate the detection probability when no shading was added, whereas shading was added for the right panels. (**b**) Mean detection probability when the person was wearing a 1/f fractal camouflage pattern using a bush/desert ROI. (**c,d**) Same as panels (**a,b**) but for an urban ROI. In general, the camouflage efficiency was better (i.e., lower detection probability) for the 1/f pattern (0.55) compared to the average-colored suit (0.85). Interestingly, when focusing on the average-colored suit in the bush/desert background, the camouflage efficiency was better when the colors were drawn from the bush/desert environment (0.46) than from the urban environment (0.88). The opposite effect was observed for the urban background, but only for the average-colored suit. That is, the camouflage efficiency was worse when the colors were drawn from the bush/desert environment (0.93) than from the urban environment (0.84). This opposing effect was not observed for the 1/f fractal pattern, which is most likely due to the deviating results for the 1/f pattern with colors drawn from  
Figure 6: **(a,b)** Mean detection probability (i.e., the confidence score generated by YOLO) as a function of object height (i.e., target distance) for each camouflage suit used in the bush desert and urban environment (collapsed over the horizontal plane), respectively. Error bars represent the standard deviation. **(c)** Overall mean detection probability for each camouflage suit used for bush/desert (left panel) and **(d)** for the urban backgrounds (right panel). Unlike the data in panels **(a,b)**, we collapsed the results over all locations with the constraint that the height of the person was between 24.37 and 201.28 pixels for both background environments (making it feasible to compare the suits across the two different background conditions). the bush/desert environment (which is expected to be due to the high contrast pattern breaking the human form rather than to the colors). As expected, the detection probability was lower when the camouflage suit's color matched the environment (0.63; e.g., urban ROI in an urban environment) than when it did not match the environment (0.77; e.g., urban ROI in a bush/desert environment). This was the case for all four camouflage suits used. This is consistent with the literature--it is easier to find an object when the color is dissimilar to the background than when it is similar to the background [33]. Figure 7 illustrates the results from the behavioral tasks in Experiment 2b. Here, Figure 7a depicts the number of responses as a function of the localization error. Trials were excluded from further analyses if the participants were not able to localize the person accurately (i.e., the localization error was >150 pixels) or when the search time was greater than 10 s. As a result, four trials were excluded where participants were not able to localize the person correctly (0.3%), and one trial was excluded because of the long search time (0.07%). Figure 7b illustrates the search performance as a function of detection probability for each image used in Experiment 3b. There was a significant negative correlation between the search time (human performance) and detection probability (YOLO performance), Spearman r = \(-\)0.65, \(p\) < 0.001, indicating that the search time increased with decreasing  
Figure 7: Results of Experiment 2b. (**a**) Number of responses as a function of the localization error. Trials were excluded from further analyses if the participants were not able to localize the person accurately (i.e., localization error > 150 pixels; see the red dotted line). (**b**) Mean search time as a function of the mean detection probability for stimulus. (**c**) Mean identification conspicuity (in degrees visual angle: dva) as a function of the mean detection probability for stimulus.