EFFICIENCY IMPROVEMENT OF ROAD SURFACE INSPECTION USING MACHINE LEARNING TECHNOLOGY

assessment of the efficiency of s.p.g.c refineries using network dea

data envelopment analysis (dea) is a powerful tool for measuring relative efficiency of organizational units referred to as decision making units (dmus). in most cases dmus have network structures with internal linking activities. traditional dea models, however, consider dmus as black boxes with no regard to their linking activities and therefore do not provide decision makers with the reasons...

Automated Visual Inspection of Road Surface Cracks

Pavement maintenance requires knowing the state of the road surface. Human inspection is the most common method for evaluating this state. Recently, the automated visual inspection has been addressed, but some important questions remain open concerning the variable ambient lighting, shadows, device synchronisation and the large amount of data. In the present paper, an automated visual inspectio...

Road surface texture inspection using high resolution transverse profile measurements

Tackling the X-ray cargo inspection challenge using machine learning

The current infrastructure for non-intrusive inspection of cargo containers cannot accommodate exploding commerce volumes and increasingly stringent regulations. There is a pressing need to develop methods to automate parts of the inspection workflow, enabling expert operators to focus on a manageable number of high-risk images. To tackle this challenge, we developed a modular framework for aut...

Automated metal surface inspection through machine vision

This paper proposes a method for automated visual inspection of metal surfaces. Firstly, the modified grey-level co-occurrence matrices of metal images are used to access the information of metal surfaces. Secondly, the difference moment and the entropy of the greylevel co-occurrence matrices are extracted as the features of the metal surfaces. Finally, the features of the inspecting images are...