Deep learning-assisted fluorescence spectroscopy for food quality and safety analysis

Trends in Food Science & Technology, Journal Year: 2024, Volume and Issue: unknown, P. 104821 - 104821

Published: Dec. 1, 2024

Language: Английский

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Optical Characteristics and Color in Foods

Published: Jan. 1, 2025

Language: Английский

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Non-Destructive Detection of Chilled Mutton Freshness Using a Dual-Branch Hierarchical Spectral Feature-Aware Network

Foods, Journal Year: 2025, Volume and Issue: 14(8), P. 1379 - 1379

Published: April 17, 2025

Precise detection of meat freshness levels is essential for food consumer safety and real-time quality monitoring. This study aims to achieve the high-accuracy chilled mutton by integrating hyperspectral imaging with deep learning methods. Although data can effectively capture changes in freshness, sparse raw spectra require optimal processing strategies minimize redundancy. Therefore, this employs a multi-stage approach enhance purity feature spectra. Meanwhile, address issues such as overlapping categories, imbalanced sample distributions, insufficient intermediate features, we propose Dual-Branch Hierarchical Spectral Feature-Aware Network (DBHSNet) detection. First, at interaction stage, PBCA module addresses drawback that global local branches conventional dual-branch framework tend perceive spectral features independently. By enabling effective information exchange bidirectional flow between two branches, injecting positional into each band, model’s awareness sequential bands enhanced. Second, fusion task-driven MSMHA introduced dynamics variation accumulation different metabolites. leveraging multi-head attention cross-scale fusion, model more captures both overall trends fine-grained details. Third, classification output dynamic loss weighting set according training epochs relative losses balance performance, mitigating impact insufficiently discriminative features. The results demonstrate DBHSNet enables precise assessment achieving up 7.59% higher accuracy than methods under same preprocessing conditions, while maintaining superior weighted metrics. Overall, offers novel provides valuable support monitoring cold-chain systems.

Language: Английский

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Rapid and chemical-free technique based on hyperspectral imaging combined with artificial intelligence for monitoring quality and shelf life of dried shrimp

Food Research International, Journal Year: 2025, Volume and Issue: unknown, P. 116422 - 116422

Published: April 1, 2025

Language: Английский

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Machine learning-optimized techniques for enhancing freshness assessment in lamb meat using hyperspectral imaging

Journal of Food Composition and Analysis, Journal Year: 2025, Volume and Issue: unknown, P. 107752 - 107752

Published: May 1, 2025

Language: Английский

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A long-term vertical displacement prediction method of concrete bridges based on meteorological shared data and optimized GRU model

Measurement, Journal Year: 2025, Volume and Issue: unknown, P. 117811 - 117811

Published: May 1, 2025

Language: Английский

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Rapid detection of mutton freshness grades and TVB-N using hyperspectral imaging with optimized machine learning and lightweight deep learning models

Journal of Food Composition and Analysis, Journal Year: 2025, Volume and Issue: unknown, P. 107815 - 107815

Published: May 1, 2025

Language: Английский

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Application of odor imaging sensor coupled with hyperspectral imaging technology in monitoring the large yellow croaker (Larimichthys crocea) freshness

Spectrochimica Acta Part A Molecular and Biomolecular Spectroscopy, Journal Year: 2024, Volume and Issue: 330, P. 125651 - 125651

Published: Dec. 25, 2024

Language: Английский

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