ArticleFoods (Basel, Switzerland)2023
Adulteration Detection of Pork in Mutton Using Smart Phone with the CBAM-Invert-ResNet and Multiple Parts Feature Fusion.
Article in Foods (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Precise Recognition of Adulterated Sliced Mutton Using Machine Vision on Mobile Phone Images.Foods (Basel, Switzerland) · 2026Article
- Non-Destructive and Real-Time Discrimination of Normal and Frozen-Thawed Beef Based on a Novel Deep Learning Model.Foods (Basel, Switzerland) · 2025Article
- Research on Pork Cut and Freshness Determination Method Based on Computer Vision.Foods (Basel, Switzerland) · 2024Article
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5 authors.
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Abstract
To achieve accurate detection the content of multiple parts pork adulterated in mutton under the effect of mutton flavor essence and colorant by RGB images, the improved CBAM-Invert-ResNet50 network based on the attention mechanism and the inversion residual was used to detect the content of pork from the back, front leg, and hind leg in adulterated mutton. The deep features of different parts extracted by the CBAM-Invert-ResNet50 were fused by feature, stitched, and combined with transfer learning, and the content of pork from mixed parts in adulterated mutton was detected. The results showed that the
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