# Object Detection for Industrial Applications: Training Strategies for AI-Based Depalletizer
## 3 Results and Discussion  
### Comparison I Results  
Considering Comparison I, Figure 5a shows the experimental results obtained on Dataset 1. For each approach, the F1-score improved when increasing the number of images. In particular, in Case 1a, the median F1-score varied from 84.0% to 92.0%, and in Case 3b, the median F1-score increased from 90.9% to 94.7%. Figure 6A,B highlight the differences in terms of the detection obtained from the models. It can be noticed that the model characterized by the highest F1-score provided a bounding box that was closer to the corners of the boxes.  
Figure 5: The boxplot of the F1-score distributions on the test sets for the comparison of a fixed scenario varying the training set size, considering _Dataset 1_ (**a**) and _Dataset 2_ (**b**). Case 1a, Case 1b, Case 2a, Case 3a, and Case 3b are the scenarios. A, B, C, D, E, F, G, and H are the numbers of the original images used for the training set. * represents statistically significant comparisons with \(p\leq 0.05\); ** represents \(p\leq 0.01\).  
Figure 5b (Dataset 2) highlights the same trend: in Case 1a, the median F1-score increased from 60.6% to 75.2% and in Case 3b from 73.3% to 83.8%. Figure 6C,D highlight the differences in terms of the detection of the models. In can be noticed that the model characterized by the highest Fl-score was more accurate during the detection. Moreover, it provided bounding boxes closer to the edges of the boxes.  
Analyzing _Dataset 1_, in Case 1a, there were statistically significant differences between A and H, A and G, and B and H with \(p\)-values of 0.0002, 0.0034, and 0.0043, respectively. Case 1b presented a statistical difference between A and G with \(p=0.0149\) and between A and H with \(p=0.0182\). For Case 3a, the F1-score was different between A and H, A and G, B and H, and C and H, in particular with \(p=0.0008\), \(p=0.0116\), \(p=0.0165\), and \(p=0.0022\). Regarding Case 3b, there were statistical differences between A and F (\(p=0.0432\)), A and G (\(p=0.0261\)), A and H (\(p=0.0016\)), B and H (\(p=0.0077\)), and C and H (\(p=0.0327\)). Regarding _Dataset 2_, in Case 1a, the F1-score distributions of A and G were statistically different (\(p=0.0053\)). For Case 1b, the statistical differences were between A and F and A and G with \(p=0.0258\) and \(p=0.0395\), respectively. Case 3b had four statistical differences, B and G (\(p=0.0099\)), A and H (\(p=0.0202\)), A and F (\(p=0.0352\)), and A and G (\(p=0.0037\)). It is worth noting that, in most of the cases, there was a significant difference between the F1-score obtained with the biggest training sets, e.g., G and H, and the F1-score obtained with the smallest training sets, e.g., A and B. Even if a growing trend can be observed for each case/approach, there were no significant differences when comparing the results achieved with the medium-sized training sets and the ones obtained with both the biggest and smallest sizes. In the authors' opinion, such results are mainly motivated by the Bonferroni correction due to the high number of multiple comparisons.  
Figure 6: (**A**) Sample result of the model fine-tuned on Dataset 1 with a median F1-score of 94.7%. (**B**) Sample result of the model fine-tuned on Dataset 1 with a median F1-score of 90.9%. (**C**) Sample result of the model fine-tuned on Dataset 2 with a median F1-score of 83.9%. (**D**) Sample result of the model fine-tuned on Dataset 2 with a median F1-score of 73.3%.  
When comparing the results of the two conditions, _Dataset 1_ and _Dataset 2_, it is worth noting that the F1-score values obtained for Dataset 2 were lower. In the authors' opinion, Dataset 2 contains boxes that are more difficult to correctly detect due to the richness of the textures and prints. This can be stated observing the results of both Cases 1a and 1b (the models were pretrained with the COCO Dataset) and Cases 3a and 3b (the models were pretrained with images of different boxes). The same difference is reported when comparing Case 2a.