Detection of Varroa destructor Infestation of Honeybees Based on Segmentation and Object Detection Convolutional Neural Networks Article Swipe
Mochen Liu
,
Mingshi Cui
,
Baohua Xu
,
Zhenguo Liu
,
Zhenghao Li
,
Zhenyuan Chu
,
Xinshan Zhang
,
Guanlu Liu
,
Xiaoli Xu
,
Yinfa Yan
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/agriengineering5040102
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.3390/agriengineering5040102
Varroa destructor infestation is a major factor leading to the global decline of honeybee populations. Monitoring the level of Varroa mite infestation in order to take timely control measures is crucial for the protection of bee colonies. Machine vision systems can achieve non-invasive Varroa mite detection on bee colonies, but it is challenged by two factors: the complex dynamic scenes of honeybees and small-scale and limited data on Varroa destructor. We design a convolutional neural network integrated with machine vision to solve these problems. To address the first challenge, we separate the image of the honeybee from its surroundings using a segmentation network, and the object-detection network YOLOX detects Varroa mites within the segmented regions. This collaboration between segmentation and object detection allows for more precise detection and reduces false positives. To handle the second challenge, we add a Coordinate Attention (CA) mechanism in YOLOX to extract a more discriminative representation of Varroa destructor and improve the confidence loss function to alleviate the problem of class imbalance. The experimental results in the bee farm showed that the evaluation metrics of our model are better than other models. Our network’s detection value for the percentage of honeybees infested with Varroa mites is 1.13%, which is the closest to the true value of 1.19% among all the detection values.
Related Topics
Concepts
Varroa destructor
Varroa
Artificial intelligence
Deformed wing virus
Varroa sensitive hygiene
Segmentation
Destructor
Convolutional neural network
Pattern recognition (psychology)
Mite
Infestation
Biology
Computer science
Ecology
Botany
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/agriengineering5040102
- https://www.mdpi.com/2624-7402/5/4/102/pdf?version=1695829262
- OA Status
- gold
- Cited By
- 11
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4387106060
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4387106060Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.3390/agriengineering5040102Digital Object Identifier
- Title
-
Detection of Varroa destructor Infestation of Honeybees Based on Segmentation and Object Detection Convolutional Neural NetworksWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-09-26Full publication date if available
- Authors
-
Mochen Liu, Mingshi Cui, Baohua Xu, Zhenguo Liu, Zhenghao Li, Zhenyuan Chu, Xinshan Zhang, Guanlu Liu, Xiaoli Xu, Yinfa YanList of authors in order
- Landing page
-
https://doi.org/10.3390/agriengineering5040102Publisher landing page
- PDF URL
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https://www.mdpi.com/2624-7402/5/4/102/pdf?version=1695829262Direct 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/2624-7402/5/4/102/pdf?version=1695829262Direct OA link when available
- Concepts
-
Varroa destructor, Varroa, Artificial intelligence, Deformed wing virus, Varroa sensitive hygiene, Segmentation, Destructor, Convolutional neural network, Pattern recognition (psychology), Mite, Infestation, Biology, Computer science, Ecology, BotanyTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
11Total citation count in OpenAlex
- Citations by year (recent)
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2025: 6, 2024: 4, 2023: 1Per-year citation counts (last 5 years)
- References (count)
-
30Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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