Abstract: Chirp ultrasonic infrared thermography is widely applied in material nondestructive testing, while its defect recognition effect is constrained by lateral thermal diffusion and image noise.

Abstract: Road crack detection is a key computer vision task that identifies and locates cracks in road surface images, which usually have an irregular shape and contain only a few pixels in width.

Abstract: Pavement crack detection is a practical and challenging task that has the ability to significantly reduce the burden of manual building and road maintenance in intelligent transportation ...

Abstract: Rail crack detection is an essential role in the safety assurance of railway transportation. However, conventional crack detection methodologies suffer from the interference of pronounced ...

Abstract: Fatigue cracks and other forms of damage can have a significant impact on the normal operation of metal facilities, necessitating the deployment of multiple sensors for monitoring within ...

Abstract: Crack detection is a fundamental effort to ensure road driving safety, aiming to detect potential safety hazards and avoid serious accidents. However, cracks can not be extracted completely ...

Thinking about learning Python? It’s a pretty popular language these days, and for good reason. It’s not super complicated, which is nice if you’re just starting out. We’ve put together a guide that ...

I skipped adding the pad to the input image when resizing, which might affect the accuracy of the model if the input image has a different aspect ratio compared to the input size of the model. Always ...

What if you could create your very own personal AI assistant—one that could research, analyze, and even interact with tools—all from scratch? It might sound like a task reserved for seasoned ...

ABSTRACT: This paper studies recent assistive technologies and AI sound detection systems that have been developed to support both the safety and communication of individuals who are deaf. It ...

This repository contains a comprehensive demonstration solution for Model Context Protocol (MCP) showcasing all three core MCP capabilities: Tools, Prompts, and Resources. Built with Python and ...