Abstract: This study investigates the potential use of ensemble learning (YOLOv9 and Mask R-CNN) and Multi-Criteria Decision Making for pothole detection system. A series of experiments were conducted, including variations in confidence thresholds, IoU thresholds, dynamic weight configurations, camera angles and MCDM criteria, to assess their effects on detection performance. The YOLOv9 model achieved a mean Average Precision (mAP) of 0.908 at 0.5 IoU and an F1 score of 0.58 at a confidence threshold of 0.282, indicating a strong balance between precision and recall. However, adjusting IoU thresholds showed that lower thresholds improved recall but resulted in false positives, while higher thresholds improved precision but reduced recall. Dynamic weight configurations were explored, with balanced weights (wY = 0.5, wM = 0.5) yielding the best overall performance, while uneven weights allowed trade-offs between precision and recall based on specific application needs. The MCDM framework refined detection outputs by evaluating pothole features such as size, position, depth, and shape. The proposed algorithm has the potential to be widely used in practical applications. Overfitting is the main drawback of the proposed algorithm, but this is dependent on the use case where the pothole detection will be used.

Ken D. Gorro, Elmo B. Ranolo, Anthony S. Ilano and Deofel P. Balijon. “Pothole Detection: A Study of Ensemble Learning and Decision Framework”. International Journal of Advanced Computer Science and Applications (IJACSA) 16.4 (2025). http://dx.doi.org/10.14569/IJACSA.2025.0160408

@article{Gorro2025,
title = {Pothole Detection: A Study of Ensemble Learning and Decision Framework},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2025.0160408},
url = {http://dx.doi.org/10.14569/IJACSA.2025.0160408},
year = {2025},
publisher = {The Science and Information Organization},
volume = {16},
number = {4},
author = {Ken D. Gorro and Elmo B. Ranolo and Anthony S. Ilano and Deofel P. Balijon}
}