FHENet: lightweight feature hierarchical exploration network for real-time rail surface defect inspection in RGB-D images

• المؤلفون الرئيسيون: Zhou, Wujie, Hong, Jiankang
• مؤلفون آخرون: School of Computer Science and Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2023
• الموضوعات: Engineering::Computer science and engineering; Boundary Extraction; Cross-Modality Exploration
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/170750

In recent years, computer vision systems have been increasingly applied to rail defect inspection. Rail defects should be identified quickly and accurately to ensure safe, stable, and fast train operations and thereby reduce the incidence of accidents and economic losses. As most existing methods fo...