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Found 6 papers, 0 papers with code
Fast Crack Detection Using Convolutional Neural Network
To improve the efficiency and reduce the labour cost of the renovation process, this study presents a lightweight Convolutional Neural Network (CNN)-based architecture to extract crack-like features, such as cracks and joints.
An Extension of BIM Using AI: a Multi Working-Machines Pathfinding Solution
In the practical implementation of a construction site, it is sensible to solve the problem with a hybrid solution; therefore, in our study, we proposed an algorithm based on a cutting-edge multi-pathfinding algorithm to enable the massive number of machines cooperation and offer the advice to modify the unreasonable part of the working site in the meantime.
A Short Review on Data Modelling for Vector Fields
On the application side, vector fields are an extremely useful type of data in empirical sciences, as well as signal processing, e. g. non-parametric transformations of 3D point clouds using 3D vector fields, the modelling of the fluid flow in earth science, and the modelling of physical fields.
KIT MOMA: A Mobile Machines Dataset
Mobile machines typically working in a closed site, have a high potential to utilize autonomous driving technology.
Fast CRDNN: Towards on Site Training of Mobile Construction Machines
In our paper, we prove this idea and show that CRDNN is always competent, with the help of transfer learning and IoT technology by field experiment, even the new machine may have a different distribution.
Optimization of Operation Strategy for Primary Torque based hydrostatic Drivetrain using Artificial Intelligence
Therefore, even with a simple regeneration process, our algorithm can improve the holistic efficiency of mobile machines up to 9% during Y cycle processes if primary torque concept is used.
