Nondestructive detection of surface defects of curved mosaic ceramics based on deep learning
Bibliographic record
Abstract
No abstract is available for this record. The assistant can identify its topic from the title, but cannot infer the study’s results.
Source: Not provided · Quality: missing
Research context
OpenAlex topics: Industrial Vision Systems and Defect Detection · 3D Surveying and Cultural Heritage · Image Processing and 3D Reconstruction
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (30)
Show source-provided references
1. Late Roman and Byzantine mosaic opaque “glass-ceramics” tesserae (5th-9th century)10.1016/j.ceramint.2016.09.033 ↗
2. Contribution of analytical techniques to determine the technologies used in the ceramic materials from the Former Workers Hospital of Maudes, Madrid (Spain)10.1016/j.jeurceramsoc.2012.09.007 ↗
3. Computer assisted glass mosaic tiling automation, Robot. Comput.-Integr
4. Production of α-TCP ceramic precision spheres for mosaic-like ceramics fabrication use
5. Effects of surface roughness and texture on the bacterial adhesion on the bearing surface of bio-ceramic joint implants: an in vitro study10.1016/j.ceramint.2019.11.139 ↗
6. Retracted article: fuzzy logic-based segmentation of manufacturing defects on reflective surfaces10.1007/s00521-017-2862-6 ↗
7. Real-time defect detection on highly reflective curved surfaces10.1016/j.optlaseng.2008.03.010 ↗
8. Ultrasonic defect detection in noisy signals by a nonconvex sparse regularization approach10.1016/j.apacoust.2023.109461 ↗
9. Damage detection of CFRP composites by electromagnetic wave nondestructive testing (EMW-NDT)10.1016/j.compscitech.2021.108839 ↗
10. Magnetic particle inspection optimization solution within the frame of NDT 4.010.3390/pr9061067 ↗
11. Enhancing flaw detection in aluminum castings by two different mixed noise removal methods10.1088/1402-4896/ab8d00 ↗
12. Application of machine vision-based NDT technology in ceramic surface defect detection – a review10.1515/mt-2021-2012 ↗
13. Deep learning for visual understanding: a review10.1016/j.neucom.2015.09.116 ↗
14. Automated surface defect detection in metals: a comparative review of object detection and semantic segmentation using deep learning10.1109/TIA.2022.3151560 ↗
15. Detection of invisible cracks in ceramic materials using by pre-trained deep convolutional neural network10.1007/s00521-021-06652-w ↗
16. The defect detection of 3D-printed ceramic curved surface parts with low contrast based on deep learning10.1016/j.ceramint.2022.09.272 ↗
17. Detection of speckle defects in alumina ceramic balls based on MobileNetV3-YOLOv5
18. Ceramic ring defect detection based on improved YOLOv5
19. A modified CenterNet for crack detection of sanitary ceramics
20. Image fusion for uninhabited airborne vehicles
21. The laplacian pyramid as a compact image code10.1109/TCOM.1983.1095851 ↗
22. A new single acquisition, two-image difference method for determining MR image SNR10.1118/1.3036118 ↗
23. A comprehensive review of past and present image inpainting methods10.1016/j.cviu.2020.103147 ↗
24. YOLOv7: trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
25. SCConv: spatial and Channel Reconstruction convolution for feature redundancy
26. Centralized feature pyramid for object detection10.1109/TIP.2023.3297408 ↗
27. Multi-scale ship detection algorithm based on YOLOv7 for complex scene SAR images10.3390/rs15082071 ↗
28. DilateFormer: multi-scale dilated transformer for visual recognition10.1109/TMM.2023.3243616 ↗
29. YOLO-SAG: an improved wildlife object detection algorithm based on YOLOv8n10.1016/j.ecoinf.2024.102791 ↗
30. FFCA-YOLO for small object detection in remote sensing images10.1109/TGRS.2024.3510781 ↗