PCB FAULT DETECTION BY USING CONVOLUTIONAL NEURAL NETWORKS Article Swipe
Reggie C. Gustilo
,
Daniel Edric Y. Ong
,
Aivan Jarell P. Chua
·
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.35741/issn.0258-2724.57.4.46
YOU?
·
· 2022
· Open Access
·
· DOI: https://doi.org/10.35741/issn.0258-2724.57.4.46
Convolutional neural network (CNN), a deep learning algorithm optimized for image processing due to its flexibility and efficiency, is proposed to be used in PCB defect detection via transfer learning. The proposed solution proved to be able to create an 85% accuracy CNN model that can predict the possible defects in each PCB image via a mobile phone. The model was then compared with previous solutions to determine whether the proposed solution was effective or not.
Related Topics
Concepts
Convolutional neural network
Computer science
Flexibility (engineering)
Deep learning
Mobile phone
Artificial intelligence
Transfer of learning
Image (mathematics)
Pattern recognition (psychology)
Fault detection and isolation
Fault (geology)
Mathematics
Telecommunications
Actuator
Seismology
Geology
Statistics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.35741/issn.0258-2724.57.4.46
- http://jsju.org/index.php/journal/article/download/1313/1303
- OA Status
- bronze
- Cited By
- 5
- References
- 18
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4295073510
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4295073510Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.35741/issn.0258-2724.57.4.46Digital Object Identifier
- Title
-
PCB FAULT DETECTION BY USING CONVOLUTIONAL NEURAL NETWORKSWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2022Year of publication
- Publication date
-
2022-08-29Full publication date if available
- Authors
-
Reggie C. Gustilo, Daniel Edric Y. Ong, Aivan Jarell P. ChuaList of authors in order
- Landing page
-
https://doi.org/10.35741/issn.0258-2724.57.4.46Publisher landing page
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https://jsju.org/index.php/journal/article/download/1313/1303Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
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bronzeOpen access status per OpenAlex
- OA URL
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https://jsju.org/index.php/journal/article/download/1313/1303Direct OA link when available
- Concepts
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Convolutional neural network, Computer science, Flexibility (engineering), Deep learning, Mobile phone, Artificial intelligence, Transfer of learning, Image (mathematics), Pattern recognition (psychology), Fault detection and isolation, Fault (geology), Mathematics, Telecommunications, Actuator, Seismology, Geology, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
5Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 2, 2024: 1, 2023: 2Per-year citation counts (last 5 years)
- References (count)
-
18Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| citation_normalized_percentile.value | 0.75201516 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |