ArticleFrontiers in nutrition2022
Intelligent grading method for walnut kernels based on deep learning and physiological indicators.
Article in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 19 citations in OpenAlex.
- Exploring Deep Learning Approaches for Walnut Phenotype Variety Classification.International journal of food science · 2025Article
- Dried shiitake mushroom grade recognition using D-VGG network and machine vision.Frontiers in nutrition · 2023Article
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Authors and funding
9 authors at 2 institutions in 1 country.
Funding
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Abstract
Walnut grading is an important step before the product enters the market. However, traditional walnut grading primarily relies on manual assessment of physiological features, which is difficult to implement efficiently. Furthermore, walnut kernel grading is, at present, relatively unsophisticated. Therefore, this study proposes a novel deep-learning model based on a spatial attention mechanism and SE-network structure to grade walnut kernels using machine vision to ensure accuracy and improve assessment efficiency. In this experiment, we found through the literature that both the lightness (
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Registered trials
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