A comprehensive review of deep learning-based hyperspectral image reconstruction for agri-food quality appraisal

Artificial Intelligence Review, Год журнала: 2025, Номер 58(4)

Опубликована: Янв. 25, 2025

Язык: Английский

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Hyperspectral Imaging Aiding Artificial Intelligence: A Reliable Approach for Food Qualification and Safety

Applied Sciences, Год журнала: 2024, Номер 14(21), С. 9821 - 9821

Опубликована: Окт. 27, 2024

Hyperspectral imaging (HSI) is one of the non-destructive quality assessment methods providing both spatial and spectral information. HSI in food safety can detect presence contaminants, adulterants, attributes, such as moisture, ripeness, microbial spoilage, a manner by analyzing signatures components wide range wavelengths with speed accuracy. However, data be quite complicated time consuming, addition to needing some special expertise. Artificial intelligence (AI) has shown immense promise for because it so powerful at coping irrelevant information, extracting key features, building calibration models. This review various machine learning (ML) approaches applied control foods. It covers basic concepts HSI, advanced preprocessing methods, strategies wavelength selection methods. The application AI increases which inspected. happens through automation contaminant detection, classification, prediction attributes. So, enable decisions real-time reducing human error inspection. paper outlines their benefits, challenges, potential improvements while again assessing validity practical usability technologies developing reliable models monitoring. concludes that integrated state-of-the-art techniques good significantly improve safety, ML algorithms have strengths, contexts they are best applied.

Язык: Английский

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The Significance of Industry 4.0 Technologies in Enhancing Various Unit Operations Applied in the Food Sector: Focus on Food Drying

Food and Bioprocess Technology, Год журнала: 2024, Номер unknown

Опубликована: Июнь 10, 2024

Язык: Английский

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New insights into the relationship between optical response and physicochemical properties in apple flesh: Hyperspectral microscope imaging technology

Food Research International, Год журнала: 2024, Номер 194, С. 114940 - 114940

Опубликована: Авг. 18, 2024

Язык: Английский

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Synergy between Artificial Intelligence and Hyperspectral Imagining—A Review

Technologies, Год журнала: 2024, Номер 12(9), С. 163 - 163

Опубликована: Сен. 13, 2024

The synergy between artificial intelligence (AI) and hyperspectral imaging (HSI) holds tremendous potential across a wide array of fields. By leveraging AI, the processing interpretation vast complex data generated by HSI are significantly enhanced, allowing for more accurate, efficient, insightful analysis. This powerful combination has to revolutionize key areas such as agriculture, environmental monitoring, medical diagnostics providing precise, real-time insights that were previously unattainable. In instance, AI-driven can enable precise crop monitoring disease detection, optimizing yields reducing waste. this technology track changes in ecosystems with unprecedented detail, aiding conservation efforts disaster response. diagnostics, AI-HSI could earlier accurate improving patient outcomes. As AI algorithms advance, their integration is expected drive innovations enhance decision-making various sectors. continued development these technologies likely open new frontiers scientific research practical applications, accessible tools wider range users.

Язык: Английский

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An overview of recent advancements in hyperspectral imaging in the egg and hatchery industry

Computers and Electronics in Agriculture, Год журнала: 2024, Номер 230, С. 109847 - 109847

Опубликована: Дек. 18, 2024

Язык: Английский

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Discrimination of unsound soybeans using hyperspectral imaging: A deep learning method based on dual-channel feature fusion strategy and attention mechanism

Food Research International, Год журнала: 2025, Номер 203, С. 115810 - 115810

Опубликована: Янв. 22, 2025

Язык: Английский

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Terahertz Multicolor Imaging of Opaque Objects Using Self-Mixing Interferometry with Quantum-Cascade Lasers

Photonics, Год журнала: 2025, Номер 12(2), С. 109 - 109

Опубликована: Янв. 25, 2025

Self-mixing interference in a terahertz quantum-cascade laser has been demonstrated to be suitable for the detection of weak signals scattered or reflected by target. This technology achieved high-sensitivity complex refractive indices, surface/interface morphologies and molecular feature spectra. Here, set lasers with different lasing frequencies is used inspect tiny amount powder concealed inside polytetrafluoroethylene tablet using self-mixing interferometry combined penetration properties waves. Multicolor spectral images were acquired, which synthesized absorption contrast obtained at frequencies. They enable spatial distribution hidden objects are totally opaque visual light allow them identified characteristics. can also obtain phase information when wave interacts tablet, showing difference between object surroundings from another dimension. Our research may provide strategy development multispectral imaging inspection trace residues.

Язык: Английский

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Hyperspectral detection of blood and melanin defects in salmon fillets

Aquaculture, Год журнала: 2025, Номер unknown, С. 742319 - 742319

Опубликована: Фев. 1, 2025

Язык: Английский

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Rapid Analysis of Starch, Sugar, and Amylose in Fresh Yam Tubers and Boiled Yam Texture Using Near-Infrared Hyperspectral Imaging and Chemometrics

Journal of Food Composition and Analysis, Год журнала: 2025, Номер unknown, С. 107425 - 107425

Опубликована: Март 1, 2025

Язык: Английский

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