Transfer Learning-based Road Damage Detection for Multiple Countries
Transfer Learning-based Road Damage Detection for Multiple Countries
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2020-08
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通讯作者：
Deeksha M. Arya;Hiroya Maeda;S. Ghosh;Durga Toshniwal;A. Mraz;Takehiro Kashiyama;Yoshihide Sekimoto Indian Institute of Technology Roorkee-Yoshihide-Sekimoto-Indian-Institute-of-Technology-1917274719;India;T. U. O. Tokyo;Japan.;EU Amazon;Luxembourg
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作者：
Deeksha M. Arya;Hiroya Maeda;S. Ghosh;Durga Toshniwal;A. Mraz;Takehiro Kashiyama;Yoshihide Sekimoto Indian Institute of Technology Roorkee-Yoshihide-Sekimoto-Indian-Institute-of-Technology-1917274719;India;T. U. O. Tokyo;Japan.;EU Amazon;Luxembourg
许多市政当局和道路管理部门都在寻求实施道路损坏的自动评估。然而，他们往往缺乏技术、专门知识和资金，无法购买最先进的设备来收集和分析道路损坏情况。尽管一些国家，如日本，已经开发出更便宜和更容易获得的基于智能手机的自动道路状况监测方法，但其他国家仍然难以找到有效的解决方案。这项工作在这方面作出了以下贡献。首先，它评估了日本模式对其他国家的可用性。其次，它提出了一个大规模的异构道路损坏数据集，包括26620图像收集来自多个国家使用智能手机。第三，我们提出了能够在一个以上的国家检测和分类道路损坏的通用模型。最后，我们为其他国家的读者，地方机构和市政当局提供建议，当一个国家发布其数据和模型的自动道路损坏检测和分类。我们的数据集可在（此https URL）。
Many municipalities and road authorities seek to implement automated evaluation of road damage. However, they often lack technology, know-how, and funds to afford state-of-the-art equipment for data collection and analysis of road damages. Although some countries, like Japan, have developed less expensive and readily available Smartphone-based methods for automatic road condition monitoring, other countries still struggle to find efficient solutions. This work makes the following contributions in this context. Firstly, it assesses the usability of the Japanese model for other countries. Secondly, it proposes a large-scale heterogeneous road damage dataset comprising 26620 images collected from multiple countries using smartphones. Thirdly, we propose generalized models capable of detecting and classifying road damages in more than one country. Lastly, we provide recommendations for readers, local agencies, and municipalities of other countries when one other country publishes its data and model for automatic road damage detection and classification. Our dataset is available at (this https URL).