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Hyperspectral Imaging

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High-throughput, rapid, and non-destructive detection of common foodborne pathogens via hyperspectral imaging coupled with deep neural networks and support vector machines.

Food research international (Ottawa, Ont.) 39967133
Foodborne pathogens such as Bacillus cereus, Staphylococcus aureus, and Escherichia coli are major causes of gastrointestinal diseases worldwide and frequently contaminate dairy products. Compared to nucleic acid detection and MALDI-TOF MS, hyperspec...
Bacillus cereus Deep Learning Discriminant Analysis Escherichia coli Food Contamination Food Microbiology Foodborne Diseases High-Throughput Screening Assays Hyperspectral Imaging Neural Networks, Computer Principal Component Analysis Staphylococcus aureus Support Vector Machine
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Characterizing Chinese saffron Origin, Age and grade using VNlR hyperspectral imaging and Machine learning.

Food research international (Ottawa, Ont.) 39967086
Saffron (Crocus sativus L.), the dried stigma, is an extremely valuable spice and medicinal herb, whose economic value is affected by geographical origin, age and grade. In this study, we proposed a method to identify saffron from different Chinese o...
Algorithms China Crocus Flowers Hyperspectral Imaging Machine Learning Spectroscopy, Near-Infrared Spices Support Vector Machine
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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 39923711
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 ...
Aged Artificial Intelligence Female Head and Neck Neoplasms Humans Hyperspectral Imaging Male Margins of Excision Middle Aged Neural Networks, Computer Squamous Cell Carcinoma of Head and Neck
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CNN-Transformer and Channel-Spatial Attention based network for hyperspectral image classification with few samples.

Neural networks : the official journal of the International Neural Network Society 40010294
Hyperspectral image classification is an important foundational technology in the field of Earth observation and remote sensing. In recent years, deep learning has achieved a series of remarkable achievements in this area. These deep learning-based h...
Algorithms Deep Learning Hyperspectral Imaging Image Processing, Computer-Assisted Neural Networks, Computer
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Exploring a universal model for predicting blueberry soluble solids content based on hyperspectral imaging and transfer learning to address spatial heterogeneity challenge.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy 39986252
Accurate assessment of soluble solid content (SSC) in blueberries is crucial for quality evaluation. However, in real production lines, blueberries are usually in random placement and the biological heterogeneity of blueberry parts can lead to spectr...
Blueberry Plants Fruit Hyperspectral Imaging Machine Learning Solubility
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Reliability of noninvasive hyperspectral tongue diagnosis for menstrual diseases using machine learning method.

Scientific reports 39979510
The outward appearance of human tongue can reflect changes in blood circulation caused by pathological states, and it has been used as an assisted method for clinical diseases diagnosis for thousands of years in China. The purpose of this study is to...
Adult Algorithms Female Humans Hyperspectral Imaging Machine Learning Menstruation Menstruation Disturbances Neural Networks, Computer Reproducibility of Results Support Vector Machine Tongue Young Adult
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Using visible and NIR hyperspectral imaging and machine learning for nondestructive detection of nutrient contents in sorghum.

Scientific reports 39972103
Nondestructive, rapid, and accurate detection of nutritional compositions in sorghum is crucial for agricultural and food industries. In our study, the crude protein, tannin, and crude fat contents of sorghum variety samples were taken as the researc...
Algorithms Hyperspectral Imaging Least-Squares Analysis Machine Learning Nutrients Nutritive Value Sorghum Spectroscopy, Near-Infrared Tannins
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Deep Learning Model Compression and Hardware Acceleration for High-Performance Foreign Material Detection on Poultry Meat Using NIR Hyperspectral Imaging.

Sensors (Basel, Switzerland) 39943610
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...
Animals Deep Learning Hyperspectral Imaging Meat Poultry Spectroscopy, Near-Infrared
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Contaminant detection in flexible polypropylene packaging waste using hyperspectral imaging and machine learning.

Waste management (New York, N.Y.) 39933416
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...
Hyperspectral Imaging Machine Learning Polypropylenes Principal Component Analysis Product Packaging Recycling Spectroscopy, Fourier Transform Infrared
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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 39923708
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...
Avena Deep Learning Edible Grain Fluorescent Dyes Food Contamination Hyperspectral Imaging
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