The DOI matches its Crossref record; 33 of the 34 references it cites were found in a registry or an index.
Automated defect inspection of LED chip using deep convolutional neural network
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“However, the above deep learning-based industrial defect detection methods do not specifically optimize the model's ability to extract and fuse features, which is crucial for defect detection.”
From A deep learning model for steel surface defect detection (2024) · cites this paper as [18]
Citations
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Cited by
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Items 201–238 of 238
Braun, G., Brokamp, M., & Klüver, C. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-23492-7_3 · Cited by 1
Yao, M., Liu, J., & Shen, Y. (2020) · Journal of Electronic Imaging · doi:10.1117/1.jei.29.4.043004
Detection of Material Defects Using Graph-Based Manifold Ranking and Heterogeneous Image Features
Zakharov, A., Bulaev, A., & Львович, Ж. А. (2020) · International Russian Automation Conference (RusAutoCon) · doi:10.1109/rusautocon49822.2020.9208119
“Significant advances in defect detection are associated with the use of deep learning [17–19].”
Background林宏達, Lin, Y.-K., & Lin, H.-D. (2020) · International journal of innovative computing, information & control
Self-citationMASS DISTRIBUTION OF DARK MATTER HALO AND SCALE EVOLUTION OF EARLY TYPE GALAXIES
", M. O. N. S. I. T. D. O., Kairatkyzy, D., Astronomy", P. D. S. I. T. S. "., Astronomy", P. A., kairatkyzy_dina90@mail.ru, & Quevedo, H. C. (2020) · NEWS OF THE NATIONAL ACADEMY OF SCIENCES OF THE REPUBLIC OF KAZAKHSTAN · doi:10.32014/2020.2518-1726.102
Automatic Reel Editing in Chip on Film Quality Control With Computer Vision
Doong, S. H. (2021) · International Journal of Systems and Service-Oriented Engineering · doi:10.4018/ijssoe.2021010101
Computer-Aided Industrial Inspection of Vehicle Mirrors Using Computer Vision Technologies
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Self-citationDefect Detection of Mechanical Design Products Using Deep Neural NetworkPreprint
Jan, M. A. (2022) · Research Square · doi:10.21203/rs.3.rs-1211827/v1
“And for different types of products and defects, different rules and algorithms need to be designed [6-10].”
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Singh, G. R., Bhargava, C., & Sharma, S. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4019678
Defect Classification in Electronic Components Using Dual-Channel Multi-Modal Convolutional Network
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“Therefore, CNNs are now getting adopted on various quality assurance tasks, such as for solar panels [4] or LED chips [5].”
BackgroundA Supervised Contrast Focus Neural Network for LED packaging defects classification
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“Deep convolutional neural networks have been successfully used in the recognition of LED defects, with early studies achieving best-in-class results [13].”
MethodDiscrepancy Constraint Learning for Industrial Unsupervised Anomaly DetectionPreprint
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A Review on Crack Detection Using Image Processing and Artificial Intelligence
Vadicherla, D., & Gupta, P. (2024) · Algorithms for intelligent systems · doi:10.1007/978-981-97-3526-6_26
High reflectivity surface defect detection system based on laser interferometry and deep learning
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“Jin et al. designed a new type of visual inspection system, which used multi-line structured light illumination to capture comprehensive surface details, and applied the unsupervised anomaly detection network PatchCore to identify abnormal parts on the steel pipe surface [6] .”
Chip Quality Inspection System based on Deep Learning
Hu, J., Gong, B., Wu, W., et al. (2024) · International Conference on Computer Vision, Image and Deep Learning (CVIDL) · doi:10.1109/cvidl62147.2024.10604231
“Simultaneously, papers[10],[11] put forward an approach that amalgamates convolutional neural networks with category activation mapping to detect defects in light-emitting diode (LED) chips.”
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Non-destructive detection of components using x-ray based on unsupervised learning
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“Lin et al. [3] proposed a convolutional neural network for light-emitting diode (LED) chip defect detection.”
Comprehensive Analysis of Machine Learning Techniques for Crack Detection
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“In recent years, deep learning has been increasingly used in engineering-based materials work [6], [7], [8], [9], [10], [11].”
Improved PCB Chip Recognition Method Based on YOLOv7-tiny
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“For instance, Huang and Gu [6] proposed an improved YOLOv3-based method for recognizing electronic components; Lin et al. [7] introduced a simple yet effective LEDNet model for surface defect detection and classification of LED chips; similarly, Shen et al. [8] proposed a lightweight convolutional…”
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“To improve the LED-chip recognition accuracy, a CNN with the class activation mapping technique is proposed to classify the LED-chip of three classes, which can effectively activate the defect area and inhibit the other non-defect area [11].”
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“A standardized preprocessing was applied to all images categorized under training before they were fed into the model [39].”
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YOLO-MDD: Addressing Inconsistent Scale Challenges in Mobile Screen Damage Detection
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“In recent years, deep learning approaches [33], [34], particularly those based on convolutional neural networks (CNNs), have demonstrated significant advantages in defect detection tasks, offering greater robustness and adaptability.”
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Metadata
- Authors
- Lin, H., Li, B., Wang, X., Shu, Y., & Niu, S.
- Affiliations
- State Key Laboratory of Digital Manufacturing Equipment and Technology (CN)
- Huazhong University of Science and Technology (CN)
- Corresponding author
- Li, Bin
- Venue
- Journal of Intelligent Manufacturing
- Published
- 2018-03-29
- Volume
- 30
- Issue
- 6
- Pages
- 2525-2534
- ISSN
- 0956-5515 (ISSN-L)
- 1572-8145
- OpenAlex
- W2794550100
- Semantic Scholar
- 358b9707c2d45c06e23a264d21390c2ed5a1d7ee
- Cited by
- 241
- References
- 34
- Citations by year
- 2026: 13 · 2025: 25 · 2024: 34 · 2023: 36 · 2022: 36 · 2021: 40 · 2020: 40 · 2019: 11 · 2018: 6
- FWCI
- 19.03
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Journal of Intelligent Manufacturing (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- The 8th batch of 3551 Optics Valley Talent Schema in East Lake Hi-tech Zone- LED chip automatic detection sorting key technology and sets of equipment development and industrialization
- Topics
- Physical Sciences › Engineering › Industrial and Manufacturing Engineering › Industrial Vision Systems and Defect Detection
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Advanced Neural Network Applications
- Physical Sciences › Engineering › Civil and Structural Engineering › Infrastructure Maintenance and Monitoring
- Keywords
- defect localization, class activation mapping, scratch marks, automated visual inspection
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