AIMC Topic: Hyperspectral Imaging
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Contaminant detection in flexible polypropylene packaging waste using hyperspectral imaging and machine learning.
Waste management (New York, N.Y.)
Feb 10, 2025
Flexible plastic packaging (FPP) constitutes one of the largest post-consumer plastic streams processed in recycling facilities. To address the key challenges of its sorting and quality control, this study developed and tested a classification proced...
Exploring the impact of lenticels on the detection of soluble solids content in apples and pears using hyperspectral imaging and one-dimensional convolutional neural networks.
Food research international (Ottawa, Ont.)
Feb 7, 2025
In this work, the effect of lenticels on the predictive performance of apple and pear soluble solids content (SSC) models developed based on hyperspectral imaging (HSI) at 380-1010 nm was investigated for the first time. Variations in the spectral pr...
Deep Learning Model Compression and Hardware Acceleration for High-Performance Foreign Material Detection on Poultry Meat Using NIR Hyperspectral Imaging.
Sensors (Basel, Switzerland)
Feb 6, 2025
Ensuring the safety and quality of poultry products requires efficient detection and removal of foreign materials during processing. Hyperspectral imaging (HSI) offers a non-invasive mechanism to capture detailed spatial and spectral information, ena...
Using near-infrared hyperspectral imaging combined with machine learning to predict the components and the origin of Radix Paeoniae Rubra.
Analytical methods : advancing methods and applications
Feb 6, 2025
The efficacy and safety of drugs are closely related to the geographical origin and quality of the raw materials. This study focuses on using near-infrared hyperspectral imaging (NIR-HSI) combined with machine learning algorithms to construct content...
Cost-efficient training of hyperspectral deep learning models for the detection of contaminating grains in bulk oats by fluorescent tagging.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Feb 4, 2025
Computer vision based on instance segmentation deep learning models offers great potential for automating many visual inspection tasks, such as the detection of contaminating grains in bulk oats, a nutrient rich grain which is well-tolerated by peopl...
Automated and explainable machine learning for monitoring lipid and protein oxidative damage in mutton using hyperspectral imaging.
Food research international (Ottawa, Ont.)
Feb 1, 2025
Current detection methods for lipid and protein oxidation using hyperspectral imaging (HSI) in conjunction with machine learning (ML) necessitate the involvement of data scientists and domain experts to adjust the model architecture and tune hyperpar...
Retrieval of nicotine content in cigar leaves by remote analysis of aerial hyperspectral combining machine learning methods.
Scientific reports
Jan 31, 2025
Cigar leaf is a special type of tobacco plant, which is the raw material for producing high-quality cigars. The content and proportion of nicotine and other composite substances of cigar leaves have a crucial impact on their quality and vary greatly ...
Enhancing surgical precision in squamous cell carcinoma of the head and neck: Hyperspectral imaging and artificial intelligence for improved margin assessment in an ex vivo setting.
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jan 30, 2025
BACKGROUND: Head and neck cancers, constituting 3-5% of all cancer cases, often require surgical resection for optimal outcomes. Achieving complete resection (R0) is crucial, but current methods, relying on white light endoscopy and microscopy, have ...
Monitoring of veterinary drug residues in mutton based on hyperspectral combined with explainable AI: A case study of OFX.
Food chemistry
Jan 27, 2025
Veterinary drug residues in meat seriously harm human health. Rapid and accurate detection of veterinary drug residues is necessary to minimize contamination. Taking ofloxacin (OFX) residues in mutton as an example, the near-infrared hyperspectral im...
Integrating hyperspectrograms with class modeling techniques for the construction of an effective expert system: Quality control of pharmaceutical tablets based on near-infrared hyperspectral imaging.
Journal of pharmaceutical and biomedical analysis
Jan 26, 2025
Near-infrared hyperspectral imaging (NIR-HSI) integrated with expert systems can support the monitoring of active pharmaceutical ingredients (APIs) and provide effective quality control of tablet formulations. However, existing quality control method...
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