AIMC Topic: Spectrum Analysis

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Towards Intraoperative Quantification of Atrial Fibrosis Using Light-Scattering Spectroscopy and Convolutional Neural Networks.

Sensors (Basel, Switzerland) Sep 9, 2021
Light-scattering spectroscopy (LSS) is an established optical approach for characterization of biological tissues. Here, we investigated the capabilities of LSS and convolutional neural networks (CNNs) to quantitatively characterize the composition a...
Humans Neural Networks, Computer Fibrosis Spectrum Analysis Myocardium Reproducibility of Results
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Davis Computational Spectroscopy Workflow-From Structure to Spectra.

Journal of chemical information and modeling Aug 27, 2021
We describe an automated workflow that connects a series of atomic simulation tools to investigate the relationship between atomic structure, lattice dynamics, materials properties, and inelastic neutron scattering (INS) spectra. Starting from the at...
Machine Learning Computer Simulation Workflow Biophysical Phenomena Spectrum Analysis
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Physical and chemical properties of edamame during bean development and application of spectroscopy-based machine learning methods to predict optimal harvest time.

Food chemistry Aug 8, 2021
This study aims to investigate the changes in physical and chemical properties of edamame during bean development and apply a spectroscopy-based machine learning (ML) technique to determine optimal harvest time. The edamame harvested at R5 (beginning...
Seeds Glycine max Machine Learning Sugars Spectrum Analysis
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Reflectance spectroscopy with operator difference for determination of behenic acid in edible vegetable oils by using convolutional neural network and polynomial correction.

Food chemistry Jul 22, 2021
A novel polynomial correction method, order-adaptive polynomial correction (OAPC), was proposed to correct reflectance spectra with operator differences, and convolutional neural network (CNN) was used to develop analysis model to predict behenic aci...
Vegetables Fatty Acids Spectrum Analysis Neural Networks, Computer Support Vector Machine Plant Oils
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Optimized adaptive Savitzky-Golay filtering algorithm based on deep learning network for absorption spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jul 16, 2021
An improved Savitzky-Golay (S-G) filtering algorithm was developed to denoise the absorption spectroscopy of nitrogen oxide (NO). A deep learning (DL) network was introduced to the traditional S-G filtering algorithm to adjust the window size and pol...
Exhalation Deep Learning Algorithms Spectrum Analysis Signal Processing, Computer-Assisted
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Extended application of deep learning combined with 2DCOS: Study on origin identification in the medicinal plant of Paris polyphylla var. yunnanensis.

Phytochemical analysis : PCA Jul 6, 2021
INTRODUCTION: Medicinal plants are very important to human health, and ensuring their quality and rapid evaluation are the current research concerns. Deep learning has a strong ability in recognition. This study extended it to the identification of m...
Plants, Medicinal Spectrum Analysis Deep Learning Liliaceae Melanthiaceae
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Diffuse reflectance spectroscopy based rapid coal rank estimation: A machine learning enabled framework.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Jul 5, 2021
This research aims at studying the ability of using diffuse reflectance spectroscopy (DRS) for discriminating or classifying coal samples into different ranks. Spectral characteristics such as the shape of the spectral profile, slope, absorption inte...
Support Vector Machine Spectrum Analysis Coal Machine Learning Algorithms
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SmartSpectrometer-Embedded Optical Spectroscopy for Applications in Agriculture and Industry.

Sensors (Basel, Switzerland) Jun 30, 2021
The ongoing digitization of industry and agriculture can benefit significantly from optical spectroscopy. In many cases, optical spectroscopy enables the estimation of properties such as substance concentrations and compositions. Spectral data can be...
Spectrum Analysis Automation Agriculture Industry Artificial Intelligence
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Quantitative analysis of lithium in brine by laser-induced breakdown spectroscopy based on convolutional neural network.

Analytica chimica acta Jun 26, 2021
In this study, a simple and effective method for accurate determination of lithium in brine samples was developed by the combination of laser induced breakdown spectroscopy (LIBS) and convolutional neural network (CNN). Our results clearly demonstrat...
Lasers Lithium Neural Networks, Computer Spectrum Analysis Salts
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Machine Learning Strategy for Soil Nutrients Prediction Using Spectroscopic Method.

Sensors (Basel, Switzerland) Jun 19, 2021
The research presented in this paper is based on the hypothesis that the machine learning approach improves the accuracy of soil properties prediction. The correlations obtained in this research are important for understanding the overall strategy fo...
Nutrients Spectrum Analysis Bayes Theorem Soil Support Vector Machine Machine Learning
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