Deep-learning system explores materials’ interiors from the outside
Maybe you can’t tell a book from its cover, but according to researchers at MIT you may now be able to do the equivalent for materials of all sorts, from…
A New Framework for Regional Traffic Volumes Estimation with Large-Scale Connected Vehicle Data and Deep Learning Method | Journal of Transportation Engineering, Part A: Systems | Vol 149, No 4
AbstractConnected vehicle (CV) data in this paper refer to the in-vehicle telematic data, including trajectories and driving events (e.g., hard braking) collected by vehicle manufacturers when vehicles are moving. Recently…
Using Images to Detect, Plan, Analyze, and Coordinate a Smart Contract in Construction | Journal of Management in Engineering | Vol 39, No 2
AbstractReliable construction workflow relies on timely discovery, analysis, and checking of compliance with contract terms, which are time consuming and inefficient tasks. Smart contracts enabled by blockchain technology have demonstrated…
Cost-Efficient Image Semantic Segmentation for Indoor Scene Understanding Using Weakly Supervised Learning and BIM | Journal of Computing in Civil Engineering | Vol 37, No 2
AbstractImage segmentation is an essential step in vision sensing and image processing. It enables the understanding of the object’s classes, spatial locations, and extents in the scene, which can be…
Encoding 3D Point Contexts for Self-Supervised Spall Classification Using 3D Bridge Point Clouds | Journal of Computing in Civil Engineering | Vol 37, No 2
AbstractGeometric features, such as normal and curvature, have been prominently used for point cloud-based unsupervised spall classification. In addition, some researchers use hand-crafted features (e.g., out-of-plane distance, eccentricity, principal curvatures in…
Automatic Damage Segmentation Framework for Buried Sewer Pipes Based on Machine Vision: Case Study of Sewer Pipes in Zhengzhou, China | Journal of Infrastructure Systems | Vol 29, No 1
AbstractAging buried sewer pipes are at risk of rupture, corrosion, scaling, and other damages, and they may cause urban waterlogging, road collapse, environmental pollution, and other urban safety problems. Therefore,…
Preprocessing of Crack Recognition: Automatic Crack-Location Method Based on Deep Learning | Journal of Materials in Civil Engineering | Vol 35, No 3
AbstractWith advancements in artificial intelligence and computer vision, machine learning has become widely employed in location and detection of road pavement distresses. Recently, recognition methods based on convolutional neural networks…
Mapping Drainage Ditches in Forested Landscapes Using Deep Learning and Aerial Laser Scanning | Journal of Irrigation and Drainage Engineering | Vol 149, No 3
IntroductionDigging drainage ditches is common forestry practice across northern European boreal forests and in some parts of North America (Lõhmus et al. 2015). Ditching helps with lowering the groundwater level in…
A Deep-Learning Classification Framework for Reducing Communication Errors in Dynamic Hand Signaling for Crane Operation | Journal of Construction Engineering and Management | Vol 149, No 2
AbstractCrane operators and signalmen play an integral role in the safe and efficient operation of cranes on a construction site. Operating a crane is a complex and demanding task that…
Network-Scale Passenger Flow Forecasting Methods in URT Based on Similarity Measurement | Journal of Transportation Engineering, Part A: Systems | Vol 149, No 2
AbstractAccurate passenger flow forecasting in urban rail transit (URT) could provide a vital reference for operators’ timely operation management. However, due to the enormous scale of the metro network, it…