Raw Data for A Lightweight Deep Learning for Real-Time Road Distress Detection on Mobile Devices

This dataset supports the research presented in the paper “A Lightweight Deep Learning for Real-Time Road Distress Detection on Mobile Devices.” The dataset contains annotated road distress images collected from diverse locations across Europe and Asia, ensuring robustness and generalizability. It includes raw images, preprocessed data, and corresponding labels used for model training, validation, and testing. The dataset is designed to facilitate the development and benchmarking of lightweight deep learning models for real-time road distress detection on resource-constrained devices, such as smartphones and mixed reality (MR) systems.

本数据集为论文《面向移动设备的轻量级深度学习实时道路病害检测》中的研究提供支持。数据集包含从欧洲和亚洲多个不同地点采集的带标注道路病害图像，确保了鲁棒性与泛化性。它涵盖用于模型训练、验证和测试的原始图像、预处理数据及对应标签。该数据集旨在促进针对智能手机和混合现实（MR）系统等资源受限设备的轻量级深度学习实时道路病害检测模型的开发与基准测试。