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相关论文: AI Driven Road Maintenance Inspection

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Bridge inspection is an important step in preserving and rehabilitating transportation infrastructure for extending their service lives. The advancement of mobile robotic technology allows the rapid collection of a large amount of…

计算机视觉与模式识别 · 计算机科学 2021-09-15 Muhammad Monjurul Karim , Ruwen Qin , Zhaozheng Yin , Genda Chen

Autonomous detection of lane markers improves road safety, and purely visual tracking is desirable for widespread vehicle compatibility and reducing sensor intrusion, cost, and energy consumption. However, visual approaches are often…

计算机视觉与模式识别 · 计算机科学 2018-08-01 Jiawei Mo , Junaed Sattar

Detecting assistance from artificial intelligence is increasingly important as they become ubiquitous across complex tasks such as text generation, medical diagnosis, and autonomous driving. Aid detection is challenging for humans,…

人工智能 · 计算机科学 2025-07-16 Tyler King , Nikolos Gurney , John H. Miller , Volkan Ustun

Transportation facilities are becoming more developed as society develops, and people's travel demand is increasing, but so are the traffic safety issues that arise as a result. And car accidents are a major issue all over the world. The…

Winter road maintenance is critical for ensuring public safety and reducing environmental impacts, yet existing methods struggle to manage large-scale routing problems effectively and mostly reply on human decision. This study presents a…

人工智能 · 计算机科学 2026-03-02 Yue Xie , Zizhen Xu , William Beazley , Fumiya Iida

Over the last decade, Computer Vision, the branch of Artificial Intelligence aimed at understanding the visual world, has evolved from simply recognizing objects in images to describing pictures, answering questions about images, aiding…

计算机视觉与模式识别 · 计算机科学 2021-11-16 Ranjay Krishna , Mitchell Gordon , Li Fei-Fei , Michael Bernstein

Autonomous robotic inspection, where a robot moves through its environment and inspects points of interest, has applications in industrial settings, structural health monitoring, and medicine. Planning the paths for a robot to safely and…

Poor roads are a major issue for cars, drivers, and pedestrians since they are a major cause of vehicle damage and can occasionally be quite dangerous for both groups of people (pedestrians and drivers), this makes road surface condition…

机器学习 · 计算机科学 2024-05-28 Makgotso Jacqueline Maotwana

Deep neural networks (DNN) have made impressive progress in the interpretation of image data, so that it is conceivable and to some degree realistic to use them in safety critical applications like automated driving. From an ethical…

Since their appearance, Smart Cities have aimed at improving the daily life of people, helping to make public services smarter and more efficient. Several of these services are often intended to provide better security conditions for…

系统与控制 · 电气工程与系统科学 2021-03-09 Andrea Atzori , Silvio Barra , Salvatore Carta , Gianni Fenu , Alessandro Sebastian Podda

Visual inspection is the predominant technique for evaluating the condition of civil infrastructure. The recent advances in unmanned aerial vehicles (UAVs) and artificial intelligence have made the visual inspections faster, safer, and more…

图像与视频处理 · 电气工程与系统科学 2022-10-25 Kareem Eltouny , Seyedomid Sajedi , Xiao Liang

E-maintenance is a technology aiming to organize and structure the ICT during the whole life cycle of the product, to develop a maintenance support system that is effective and efficient. A current challenge of E-maintenance is the…

人机交互 · 计算机科学 2014-07-11 Allan Oliveira , Regina Araujo

In this work, we investigate whether humans can manually generate high-quality robot paths for optical inspections. Typically, automated algorithms are used to solve the inspection planning problem. The use of automated algorithms implies…

机器人学 · 计算机科学 2019-09-16 Boris Bogaerts , Seppe Sels , Steve Vanlanduit , Rudi Penne

The usage of Unmanned Aerial Vehicles (UAVs) in the context of structural health inspection is recently gaining tremendous popularity. Camera mounted UAVs enable the fast acquisition of a large number of images often used for mapping, 3D…

计算机视觉与模式识别 · 计算机科学 2021-10-12 Alon Oring

A significant portion of driving hazards is caused by human error and disregard for local driving regulations; Consequently, an intelligent assistance system can be beneficial. This paper proposes a novel vision-based modular package to…

计算机视觉与模式识别 · 计算机科学 2023-03-30 Amirhossein Kazerouni , Amirhossein Heydarian , Milad Soltany , Aida Mohammadshahi , Abbas Omidi , Saeed Ebadollahi

Artificial intelligence (AI) and computer vision are transforming transportation data collection. This study introduces an AI-enabled analytics framework leveraging existing CCTV infrastructure to evaluate the impact of soft interventions,…

人工智能 · 计算机科学 2026-05-08 Vinit Katariya , Seungjin Kim , Curtis Craig , Nichole Morris , Hamed Tabkhi

Automated vehicles promise to enhance transportation safety and efficiency. However, ensuring their reliability in real-world conditions remains challenging, particularly due to rare and unexpected situations known as edge cases. While…

Safety-critical infrastructures, such as bridges, are periodically inspected to check for existing damage, such as fatigue cracks and corrosion, and to guarantee the safe use of the infrastructure. Visual inspection is the most frequent…

计算机视觉与模式识别 · 计算机科学 2024-03-29 Andrii Kompanets , Remco Duits , Davide Leonetti , Nicky van den Berg , H. H. , Snijder

While automated driving is often advertised with better-than-human driving performance, this work reviews that it is nearly impossible to provide direct statistical evidence on the system level that this is actually the case. The amount of…

机器学习 · 计算机科学 2021-12-10 Hanno Gottschalk , Matthias Rottmann , Maida Saltagic

Usability inspection is a well-established technique for identifying interaction issues in software interfaces, thereby contributing to improved product quality. However, it is a costly process that requires time and specialized knowledge…

软件工程 · 计算机科学 2025-10-21 Luis F. G. Campos , Leonardo C. Marques , Walter T. Nakamura