AIMC Topic: Hyperspectral Imaging

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Understanding mass spectrometry images: complexity to clarity with machine learning.

Biopolymers Sep 16, 2020
The application of artificial intelligence and machine learning to hyperspectral mass spectrometry imaging (MSI) data has received considerable attention over recent years. Various methodologies have shown great promise in their ability to handle the...
Humans Artificial Intelligence Machine Learning Mass Spectrometry Hyperspectral Imaging Algorithms Animals
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Adoption of Machine Learning in Intelligent Terrain Classification of Hyperspectral Remote Sensing Images.

Computational intelligence and neuroscience Sep 1, 2020
To overcome the difficulty of automating and intelligently classifying the ground features in remote-sensing hyperspectral images, machine learning methods are gradually introduced into the process of remote-sensing imaging. First, the PaviaU, Botswa...
Classification Support Vector Machine Hyperspectral Imaging Machine Learning
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Detection and identification of Cannabis sativa L. using near infrared hyperspectral imaging and machine learning methods. A feasibility study.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Apr 21, 2020
Remote identification of illegal plantations of Cannabis sativa Linnaeus is an important task for the Brazilian Federal Police. The current analytical methodology is expensive and strongly dependent on the expertise of the forensic investigator. A fa...
Cannabis Hyperspectral Imaging Cheminformatics Principal Component Analysis Feasibility Studies Reproducibility of Results Sensitivity and Specificity Spectroscopy, Near-Infrared Machine Learning Plant Leaves Brazil
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Unified Classification of Bacterial Colonies on Different Agar Media Based on Hyperspectral Imaging and Machine Learning.

Molecules (Basel, Switzerland) Apr 14, 2020
A universal method by considering different types of culture media can enable convenient classification of bacterial species. The study combined hyperspectral technology and versatile chemometric algorithms to achieve the rapid and non-destructive cl...
Hyperspectral Imaging Bacterial Typing Techniques Machine Learning Algorithms Support Vector Machine Colony Count, Microbial Models, Theoretical
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Hyperspectral imaging for accurate determination of rice variety using a deep learning network with multi-feature fusion.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Mar 6, 2020
The phenomena of rice adulteration and shoddy rice arise continuously in high-quality rice and reduce the interests of producers, consumers and traders. Hyperspectral imaging (HSI) was conducted to determine rice variety using a deep learning network...
Spectroscopy, Near-Infrared Deep Learning Image Processing, Computer-Assisted Principal Component Analysis China Geography Neural Networks, Computer Oryza Entropy Algorithms Hyperspectral Imaging
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Hyperspectral imaging combined with machine learning as a tool to obtain high-throughput plant salt-stress phenotyping.

The Plant journal : for cell and molecular biology Dec 9, 2019
The rapid selection of salinity-tolerant crops to increase food production in salinized lands is important for sustainable agriculture. Recently, high-throughput plant phenotyping technologies have been adopted that use plant morphological and physio...
Abelmoschus High-Throughput Screening Assays Crops, Agricultural Deep Learning Genetic Association Studies Salt Stress Machine Learning Salt-Tolerant Plants Phenotype Hyperspectral Imaging Crop Production
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Investigating potato late blight physiological differences across potato cultivars with spectroscopy and machine learning.

Plant science : an international journal of experimental plant biology Nov 13, 2019
Understanding plant disease resistance is important in the integrated management of Phytophthora infestans, causal agent of potato late blight. Advanced field-based methods of disease detection that can identify infection before the onset of visual s...
Plant Diseases Solanum tuberosum Remote Sensing Technology Machine Learning Spectrum Analysis Hyperspectral Imaging Plant Leaves Phytophthora infestans
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Comparison between chemometrics and machine learning for the prediction of macronutrients in cheese using Imaging spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 15, 2025
Traditional methods for assessing cheese's nutritional content are often labor-intensive, destructive, and environmentally taxing. This study explores the non-destructive spectral imaging technique, also called Hyperspectral Imaging (HSI) combined wi...
Machine Learning Least-Squares Analysis Cheese Fats Chemometrics Nutrients Hyperspectral Imaging
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Hyperspectral imaging and machine learning for quality assessment of apples with different bagging types.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Dec 15, 2025
This study examined how different bagging types (unbagged, mesh-bagged, and paper-bagged) affect the internal and external quality of fruits. Spectral images of 307 apples were collected using a visible-near infrared hyperspectral imaging system, and...
Food Quality Hyperspectral Imaging Malus Machine Learning Color Fruit Algorithms
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Predicting the composition of aroma components in Baijiu using hyperspectral imaging combined with a replication allocation strategy-enhanced stacked ensemble learning model.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Nov 15, 2025
Ester and acid aroma compounds are crucial components affecting the fragrance of Baijiu, and their composition can endow the Baijiu with a fruity, acidic, floral, or roasted aroma. This study aims to quantitatively detect the ester and acid content i...
Machine Learning Acids Hyperspectral Imaging Soy Foods Ensemble Learning Odorants Esters
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