WebMar 17, 2024 · This paper provides a report on our solution including model selection, tuning strategy and results obtained for Global Road Damage Detection Challenge. This Big … WebMar 9, 2024 · Best alternative to these methods would be an smart detector which detects damages using their recorded images or video. Apart from the road infrastructure, a road damage detector will also be useful in self driving cars to detect some potholes or other disturbance in their way and try to avoid them. 2. Dataset.

Global Road Damage Detection: State-of-the-art Solutions

WebMay 12, 2024 · For instance, the Global Road Damage Detection Challenge (GRDDC'2024), organized as an IEEE Big Data Cup in 2024, utilized the dataset RDD2024 to evaluate the road damage detection models proposed by participants [5,6]. Go to: 1. Data Description. bird cage mr.children

CNN Model & Tuning for Global Road Damage Detection

WebSep 15, 2024 · An F1 score of 61.86% and an F1 score of 60.92 were achieved on the two test sets, and the comparison with the results submitted on the Global Road Damage Detection Challenge'2024 is shown in ... WebAbstract. This article presents the solution that we use in the Global Road Damage Detection Challenge 2024, which is designed to recognize the road damages present in an image captured from three countries: India, Japan, and Czech. In this challenge, Cascade R-CNN is selected as a baseline model to detect objects in images. WebWe also experiment with these approaches using the Global Road Damage Detection Challenge 2024, A Track in the IEEE Big Data 2024 Big Data Cup Challenge dataset. The results show that the X101-FPN base model for Faster R-CNN with Detectron2's default configurations is efficient and general enough to be transferable to different countries in ... dalrymple bay infrastructure prospectus