Deep Learning for Automated Visual Inspection in Manufacturing and Maintenance: A Survey of Open-Access Papers

N Hütten, M Alves Gomes, F Hölken… - Applied System …, 2024 - mdpi.com
Quality assessment in industrial applications is often carried out through visual inspection,
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 …

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 …

LUVS-Net: A Lightweight U-Net Vessel Segmentor for Retinal Vasculature Detection in Fundus Images

MT Islam, Z LI, K MAEDA, R TOGO, T OGAWA… - Intelligence, Informatics …, 2023 - jstage.jst.go.jp
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 …

[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 …

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 …

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 …

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 …