This paper describes a pixel-wise detection algorithm to reconstruct rock cracks using CT
images. Through reviewing the shortcomings of previous studies, a pixel-level labeled …

Pixel-level detection and segmentation of pavement cracks is a crucial but challenging task.
Current deep learning methods mainly target larger cracks, often overlooking tiny cracks …

Crack detection is essential for ensuring road safety and preserving the integrity of
infrastructure. As intelligent transportation systems mature, vehicles equipped with crack …

Although real-time semantic segmentation of pavement cracks is crucial for road evaluation
and maintenance decision-making, it is a challenging task due to low operational efficiency …

Concrete cracks pose significant challenges to infrastructure maintenance and safety.
Traditional methods for detecting cracks suffer from inefficiency and subjectivity. Deep …

Conducting real-world train crash experiments is the most straightforward and effective
method to research the train's crashworthiness and enhance passive safety protection. As a …

Detecting cracks is a crucial task to ensure the safety of engineering. However, the
complexity of the crack background and the highly uneven pixel ratio between the crack and …

Crack detection is an important task to ensure structural safety. Traditional manual detection
is extremely time-consuming and labor-intensive. However, existing deep learning-based …

Accurate and efficient pixel-level pavement crack detection is critically important for traffic
management. Despite the improved performance on current deep learning-based detection …

The accurate detection and segmentation of pavement distresses, particularly tiny and small
cracks, are critical for early intervention and preventive maintenance in transportation …