NovaNet: A Novel Method for Enhanced Pothole Detection on Road

Potholes present a pervasive and escalating challenge for urban infrastructure, posing significant risks to vehicle safety and necessitating substantial maintenance expenditures. NovaNet is a novel convolutional neural network architecture specifically designed to address this problem by enabling precise pothole detection on road surfaces. Incorporating elements such as spatial awareness, gated convolutional operations, and attention mechanisms, NovaNet offers enhanced detection capabilities. Its multi-scale feature fusion block adeptly combines semantic details from various resolutions, ensuring comprehensive segmentation. Adversarially trained to bolster resilience, NovaNet performs robustly under diverse conditions, achieving a state-of-the-art Intersection over Union (IoU) score of 0.762. This precision in identifying and localizing road defects positions NovaNet as an invaluable tool for improving road safety and aiding in the proactive maintenance of urban infrastructure.