AIMC Topic: Hyperspectral Imaging

Clear Filters Showing 61 to 70 of 210 articles

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.) Jan 7, 2025
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...
Support Vector Machine Escherichia coli Staphylococcus aureus Neural Networks, Computer Deep Learning Principal Component Analysis Discriminant Analysis High-Throughput Screening Assays Food Microbiology Foodborne Diseases Food Contamination Hyperspectral Imaging Bacillus cereus
View on PubMed DOI

Seed Protein Content Estimation with Bench-Top Hyperspectral Imaging and Attentive Convolutional Neural Network Models.

Sensors (Basel, Switzerland) Jan 7, 2025
Wheat is a globally cultivated cereal crop with substantial protein content present in its seeds. This research aimed to develop robust methods for predicting seed protein concentration in wheat seeds using bench-top hyperspectral imaging in the visi...
Machine Learning Triticum Spectroscopy, Near-Infrared Convolutional Neural Networks Hyperspectral Imaging Neural Networks, Computer Image Processing, Computer-Assisted Support Vector Machine Plant Proteins Seeds
View on PubMed DOI

Characterizing Chinese saffron Origin, Age and grade using VNlR hyperspectral imaging and Machine learning.

Food research international (Ottawa, Ont.) Jan 2, 2025
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...
Spices China Support Vector Machine Hyperspectral Imaging Crocus Flowers Machine Learning Algorithms Spectroscopy, Near-Infrared
View on PubMed DOI

Quality prediction of air-cured cigar tobacco leaf using region-based neural networks combined with visible and near-infrared hyperspectral imaging.

Scientific reports Dec 28, 2024
Visible and Near-infrared hyperspectral imaging (VNIR-HSI) combined with machine learning has shown its effectiveness in various detection applications. Specifically, the quality of cigar tobacco leaves undergoes subtle changes due to environmental d...
Spectroscopy, Near-Infrared Deep Learning Nitrogen Tobacco Products Plant Leaves Hyperspectral Imaging Nicotiana Neural Networks, Computer Chlorophyll
View on PubMed DOI

Determination and visualization of moisture content in Camellia oleifera seeds rapidly based on hyperspectral imaging combined with deep learning.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 27, 2024
Moisture content (MC) is crucial for the storage, transportation, and processing of Camellia oleifera seeds. The purpose of this study was to investigate the feasibility for detecting MC in Camellia oleifera seeds using visible near-infrared hyperspe...
Hyperspectral Imaging Seeds Neural Networks, Computer Camellia Least-Squares Analysis Deep Learning Algorithms Water Spectroscopy, Near-Infrared Support Vector Machine
View on PubMed DOI

Machine Vision with a CMOS-Based Hyperspectral Imaging Sensor Enables Sensing Meat Freshness.

ACS sensors Dec 25, 2024
Imaging spectral information of materials and analysis of its properties have become an intriguing tool for consumer electronics used for food inspection, beauty care, etc. Those sensory physical quantities are difficult to quantify. Hyperspectral im...
Semiconductors Machine Learning Meat Hyperspectral Imaging Animals
View on PubMed DOI

Exploring hyperspectral anomaly detection with human vision: A small target aware detector.

Neural networks : the official journal of the International Neural Network Society Dec 15, 2024
Hyperspectral anomaly detection (HAD) aims to localize pixel points whose spectral features differ from the background. HAD is essential in scenarios of unknown or camouflaged target features, such as water quality monitoring, crop growth monitoring ...
Visual Perception Image Processing, Computer-Assisted Hyperspectral Imaging Neural Networks, Computer Algorithms Humans
View on PubMed DOI

Enhancing land cover object classification in hyperspectral imagery through an efficient spectral-spatial feature learning approach.

PloS one Dec 5, 2024
The classification of land cover objects in hyperspectral imagery (HSI) has significantly advanced due to the development of convolutional neural networks (CNNs). However, challenges such as limited training data and high dimensionality negatively im...
Neural Networks, Computer Image Processing, Computer-Assisted Principal Component Analysis Algorithms Hyperspectral Imaging
View on PubMed DOI

Detection of Apple Proliferation Disease Using Hyperspectral Imaging and Machine Learning Techniques.

Sensors (Basel, Switzerland) Dec 4, 2024
Apple proliferation is among the most important diseases in European fruit production. Early and reliable detection enables farmers to respond appropriately and to prevent further spreading of the disease. Traditional phenotyping approaches by human ...
Image Processing, Computer-Assisted Plant Leaves Plant Diseases Malus Hyperspectral Imaging Machine Learning Algorithms
View on PubMed DOI

A green and efficient method for detecting nicosulfuron residues in field maize using hyperspectral imaging and deep learning.

Journal of hazardous materials Nov 30, 2024
Accurate and rapid detection of nicosulfuron herbicide residues in field-grown maize is essential for implementing chemical remediation and optimizing spraying strategies. However, current detection methods are costly and time-consuming. This study a...
Pesticide Residues Neural Networks, Computer Pyridines Sulfonylurea Compounds Deep Learning Plant Leaves Herbicides Zea mays Hyperspectral Imaging
View on PubMed DOI
Popular Topics
Recent Journals