AMFF-YOLOX: Towards an Attention Mechanism and Multiple Feature Fusion Based on YOLOX for Industrial Defect Detection Article Swipe
Yu Chen
,
Yongwei Tang
,
Huijuan Hao
,
Jun Zhou
,
Huimiao Yuan
,
Yu Zhang
,
Yuanyuan Zhao
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/electronics12071662
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/electronics12071662
Industrial defect detection has great significance in product quality improvement, and deep learning methods are now the dominant approach. However, the volume of industrial products is enormous and mainstream detectors are unable to maintain a high accuracy rate during rapid detection. To address the above issues, this paper proposes AMFF-YOLOX, an improved industrial defect detector based on YOLOX. The proposed method can reduce the activation function and normalization operation of the bottleneck in the backbone network, and add an attention mechanism and adaptive spatial feature fusion within the feature extraction network to enable the network to better focus on the object. Ultimately, the accuracy of the prediction is enhanced without excessive loss of speed in network prediction, with competitive performance compared to mainstream detectors. Experiments show that the proposed method in this paper achieves 61.06% (85.00%) [email protected]:0.95 ([email protected]) in the NRSD-MN dataset, 51.58% (91.09%) is achieved in the PCB dataset, and 49.08% (80.48%) is achieved in the NEU-DET dataset. A large number of comparison and ablation experiments validate the effectiveness and competitiveness of the model in industrial defect detection scenarios.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/electronics12071662
- https://www.mdpi.com/2079-9292/12/7/1662/pdf?version=1680268078
- OA Status
- gold
- Cited By
- 8
- References
- 45
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4362471027
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- OpenAlex ID
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https://openalex.org/W4362471027Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/electronics12071662Digital Object Identifier
- Title
-
AMFF-YOLOX: Towards an Attention Mechanism and Multiple Feature Fusion Based on YOLOX for Industrial Defect DetectionWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-03-31Full publication date if available
- Authors
-
Yu Chen, Yongwei Tang, Huijuan Hao, Jun Zhou, Huimiao Yuan, Yu Zhang, Yuanyuan ZhaoList of authors in order
- Landing page
-
https://doi.org/10.3390/electronics12071662Publisher landing page
- PDF URL
-
https://www.mdpi.com/2079-9292/12/7/1662/pdf?version=1680268078Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
-
https://www.mdpi.com/2079-9292/12/7/1662/pdf?version=1680268078Direct OA link when available
- Concepts
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Computer science, Bottleneck, Normalization (sociology), Artificial intelligence, Detector, Object detection, Deep learning, Feature extraction, Pattern recognition (psychology), Data mining, Feature (linguistics), Embedded system, Telecommunications, Linguistics, Sociology, Philosophy, AnthropologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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8Total citation count in OpenAlex
- Citations by year (recent)
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2025: 1, 2024: 4, 2023: 3Per-year citation counts (last 5 years)
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45Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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