ArticleFrontiers in plant science2022
YOLOF-Snake: An Efficient Segmentation Model for Green Object Fruit.
Article in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Deep learning based instance segmentation of mandarin fruit slices for precision assessment and morphological quantification.Scientific reports · 2026Article
- GC Snakes: An Efficient and Robust Segmentation Model for Hot Forging Images.Sensors (Basel, Switzerland) · 2024Article
- Feasibility Study on the Classification of Persimmon Trees' Components Based on Hyperspectral LiDAR.Sensors (Basel, Switzerland) · 2023Article
- Orchard monitoring based on unmanned aerial vehicles and image processing by artificial neural networks: a systematic review.Frontiers in plant science · 2023Review
- Apple detection and instance segmentation in natural environments using an improved Mask Scoring R-CNN Model.Frontiers in plant science · 2022Article
- SE-COTR: A Novel Fruit Segmentation Model for Green Apples Application in Complex Orchard.Plant phenomics (Washington, D.C.) · 2022Article
- A method for locating soil monitoring points in greenhouse cultivation based on DeeplabV3.Science progressArticle
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Authors and funding
7 authors.
Funding
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Abstract
Accurate detection and segmentation of the object fruit is the key part of orchard production measurement and automated picking. Affected by light, weather, and operating angle, it brings new challenges to the efficient and accurate detection and segmentation of the green object fruit under complex orchard backgrounds. For the green fruit segmentation, an efficient YOLOF-snake segmentation model is proposed. First, the ResNet101 structure is adopted as the backbone network to achieve feature extraction of the green object fruit. Then, the C5 feature maps are expanded with receptive fields and the decoder is used for classification and regression. Besides, the center point in the regression box is employed to get a diamond-shaped structure and fed into an additional Deep-snake network, which is adjusted to the contours of the target fruit to achieve fast and accurate segmentation of green fruit. The experimental results show that YOLOF-snake is sensitive to the green fruit, and the segmentation accuracy and efficiency are significantly improved. The proposed model can effectively extend the application of agricultural equipment and provide theoretical references for other fruits and vegetable segmentation.
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