Results 81 to 90 of about 7,467,907 (193)
Lightweight Pyramid Cross-Attention Network for No-Service Rail Surface Defect Detection
IEEE AccessVision-based rail defect detection plays a crucial role in ensuring the safety and efficiency of railway transportation systems. However, many existing methods face challenges such as high parameters, complex computation, slow inspection speed, and low ...
Sixu Guo +4 more
doaj +1 more source
Structural Concrete, EarlyView.Abstract Automating bridge inspections requires more than detecting individual damage instances. It demands systems capable of describing, contextualizing, and interpreting damage in an inspection‐relevant manner. Conventional computer vision approaches, such as object detection and segmentation, primarily address visual recognition tasks and are ...
Rona Firdes Çelik +2 more
wiley +1 more source
An integrated texture and depth isomorphic imaging and cross‐modal network for rail surface defect detection and measurement [PDF]
Rail defects significantly impact train operations, even posing serious safety risks. Existing methods can automatically collect images from the rail surface and identify apparent defects while facing challenges such as high false positive rates ...
Li, Jun +9 more
core +1 more source
Do the public take action when a severe snow warning is issued?
Weather, EarlyView.Extreme weather events pose significant risks to the population, making timely warnings essential for preparedness. The UK Met Office’s National Severe Weather Warning Service (NSWWS) has issued impact‐based alerts for over a decade, yet evaluations of their effectiveness remain limited.
Helen Dacre, Rachel McCloy, Joi Alon
wiley +1 more source
Rail Surface Defect Detection and Severity Analysis using CNNs on Camera and Axle Box Acceleration Data [PDF]
, 2023 Rail surface defect detection is a relevant problem in the field of data-driven railway maintenance. Artificial intelligence and neural networks (NN) for axle box acceleration (ABA) or camera data show great potential for defect detection and ...
Lähns, Alexander +4 more
core
Real-Time Analysis of Track Surface Defect Images Using WT-YOLO12
IEEE Open Journal of Instrumentation and MeasurementThe rapid and precise defect detection of rail surface defects is critical for railway operational safety. The conventional inspection methods, however, are often labor-intensive, resource-consuming, and vulnerable to noise.
Guanlin Zhang +4 more
doaj +1 more source
High Voltage, EarlyView.ABSTRACT This paper provides an overview of high‐temperature superconducting (HTS) cables in DC systems, with a focus on their deployment in high‐voltage DC (HVDC) networks. The assessment of HTS cable properties—such as extremely low electrical resistance, high current‐carrying capacity and a compact geometry—and their comparison with those of ...
Mohammad Hossein Mousavi +2 more
wiley +1 more source
IET Collaborative Intelligent ManufacturingIndustrial defect detection is an important part of intelligent manufacturing, and Internet of things (IoT)‐based defect detection is receiving more and more attention. Although deep learning (DL) can help defect detection reduce the cost and improve the
Han Yue +5 more
doaj +1 more source
International Journal of Urban and Regional Research, EarlyView.Abstract From desert ski resorts to subtropical Winter Games, there is a global proliferation of ‘mission‐impossible’ mega‐projects. The prevailing frameworks of city branding and urban entrepreneurism fail to explain the political logics behind these seemingly irrational projects.
Yiqiu Liu, Sven Daniel Wolfe
wiley +1 more source
Ultrasonic Guided Waves-Based Monitoring of Rail Head: Laboratory and Field Tests
Advances in Civil Engineering, 2010 Recent train accidents have reaffirmed the need for developing a rail defect detection system more effective than that currently used. One of the most promising techniques in rail inspection is the use of ultrasonic guided waves and noncontact probes.
Piervincenzo Rizzo +6 more
doaj +1 more source