In the expanding landscape of artificial intelligence, object detection (OD) models serve as the structural backbone for mission-critical technologies like autonomous driving, medical diagnostics, and automated surveillance. However, these systems face a critical vulnerability: . These physically reproducible, localized distortions can cause deep learning models to completely overlook or misclassify primary objects.
