Instance Segmentation of Tea Garden Roads Based on an Improved YOLOv8n-seg Model Article Swipe
Weibin Wu
,
Zhaokai He
,
Junlin Li
,
Tianci Chen
,
Qing Luo
,
Yuanqiang Luo
,
Weihui Wu
,
Zhenbang Zhang
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/agriculture14071163
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.3390/agriculture14071163
In order to improve the efficiency of fine segmentation and obstacle removal in the road of tea plantation in hilly areas, a lightweight and high-precision DR-YOLO instance segmentation algorithm is proposed to realize environment awareness. Firstly, the road data of tea gardens in hilly areas were collected under different road conditions and light conditions, and data sets were generated. YOLOv8n-seg, which has the highest operating efficiency, was selected as the basic model. The MSDA-CBAM and DR-Neck feature fusion network were added to the YOLOv8-seg model to improve the feature extraction capability of the network and the feature fusion capability and efficiency of the model. Experimental results show that, compared with the YOLOv8-seg model, the DR-YOLO model proposed in this study has 2.0% improvement in [email protected] and 1.1% improvement in Precision. In this study, the DR-YOLO model is pruned and quantitatively compressed, which greatly improves the model inference speed with little reduction in AP. After deploying on Jetson, compared with the YOLOv8n-seg model, the Precision of DR-YOLO is increased by 0.6%, the [email protected] is increased by 1.6%, and the inference time is reduced by 17.1%, which can effectively improve the level of agricultural intelligent automation and realize the efficient operation of the instance segmentation model at the edge.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/agriculture14071163
- https://www.mdpi.com/2077-0472/14/7/1163/pdf?version=1721302790
- OA Status
- gold
- Cited By
- 10
- References
- 30
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4400734158
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Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4400734158Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.3390/agriculture14071163Digital Object Identifier
- Title
-
Instance Segmentation of Tea Garden Roads Based on an Improved YOLOv8n-seg ModelWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-07-16Full publication date if available
- Authors
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Weibin Wu, Zhaokai He, Junlin Li, Tianci Chen, Qing Luo, Yuanqiang Luo, Weihui Wu, Zhenbang ZhangList of authors in order
- Landing page
-
https://doi.org/10.3390/agriculture14071163Publisher landing page
- PDF URL
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https://www.mdpi.com/2077-0472/14/7/1163/pdf?version=1721302790Direct link to full text PDF
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YesWhether a free full text is available
- OA status
-
goldOpen access status per OpenAlex
- OA URL
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https://www.mdpi.com/2077-0472/14/7/1163/pdf?version=1721302790Direct OA link when available
- Concepts
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Segmentation, Computer science, Feature (linguistics), Obstacle, Reduction (mathematics), Artificial intelligence, Inference, Computer vision, Mathematics, Geography, Geometry, Archaeology, Philosophy, LinguisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
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10Total citation count in OpenAlex
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2025: 7, 2024: 3Per-year citation counts (last 5 years)
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30Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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