Fig. 5: End-to-end deployment and ablation study of MobiLiteNet framework.
From: Lightweight deep learning for real-time road distress detection on mobile devices
a Process flow for mobile deployment and inference. Icons by Lucas Rathgeb, Puspito, Camallia Marroh, Good Wife, Dan’s, Ali Mahmudi, Ainul Abib, and Reza Nur from the Noun Project (CC BY 3.0). b Ablation study of model optimization in MobiLiteNet framework. c Confusion matrices for ablation study models: BR broken pavement marking, LO longitudinal crack, MA alligator crack, TR transverse crack.
