Deep Learning for Automated Visual Inspection in Manufacturing and Maintenance: A Survey of Open-Access Papers
Quality assessment in industrial applications is often carried out through visual inspection,
usually performed or supported by human domain experts. However, the manual visual …
usually performed or supported by human domain experts. However, the manual visual …
AI-based rock strength assessment from tunnel face images using hybrid neural networks
L Liu, Z Song, P Zhou, XH He, L Zhao - Scientific Reports, 2024 - nature.com
In geological engineering and related fields, accurately and quickly identifying lithology and
assessing rock strength are crucial for ensuring structural safety and optimizing design …
assessing rock strength are crucial for ensuring structural safety and optimizing design …
HoloForkNet: digital hologram reconstruction via multibranch neural network
AS Svistunov, DA Rymov, RS Starikov… - Applied Sciences, 2023 - mdpi.com
Reconstruction of 3D scenes from digital holograms is an important task in different areas of
science, such as biology, medicine, ecology, etc. A lot of parameters, such as the object's …
science, such as biology, medicine, ecology, etc. A lot of parameters, such as the object's …
LUVS-Net: A Lightweight U-Net Vessel Segmentor for Retinal Vasculature Detection in Fundus Images
Detection of subway tunnel distress is a crucial task for ensuring public safety. It is typically
performed manually by technical workers, which has become increasingly expensive due to …
performed manually by technical workers, which has become increasingly expensive due to …
[HTML][HTML] Efficient Detection of Apparent Defects in Subway Tunnel Linings Based on Deep Learning Methods
A Zheng, S Qi, Y Cheng, D Wu, J Zhu - Applied Sciences, 2024 - mdpi.com
High-precision and rapid detection of apparent defects in subway tunnel linings is crucial for
ensuring the structural integrity of tunnels and the safety of train operations. However …
ensuring the structural integrity of tunnels and the safety of train operations. However …
MFF-YOLO: An Accurate Model for Detecting Tunnel Defects Based on Multi-Scale Feature Fusion
A Zhu, B Wang, J **e, C Ma - Sensors, 2023 - mdpi.com
Tunnel linings require routine inspection as they have a big impact on a tunnel's safety and
longevity. In this study, the convolutional neural network was utilized to develop the MFF …
longevity. In this study, the convolutional neural network was utilized to develop the MFF …
A new small target defect detection algorithm for solar panels based on improved YOLOV7
Q Ren, Y Zhang, L Wen - Nondestructive Testing and Evaluation, 2025 - Taylor & Francis
ABSTRACT Surface Defect Detection (SDD) is an important means to ensure product quality
in industrial production. Accompanied by the rapid development of artificial intelligence …
in industrial production. Accompanied by the rapid development of artificial intelligence …
Automated subway tunnel lining crack classification and detection based on two-step sequential convolutional neural network
C Tang, YF Liu, BL Li, L Tang, JS Fan - Journal of Civil Structural Health …, 2024 - Springer
Crack identification of subway tunnel lining is integral for preventive maintenance. The
industry urgently requires accurate and efficient automation methods to handle the …
industry urgently requires accurate and efficient automation methods to handle the …