AIMC Topic: Spectrum Analysis

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Comparison of Convolutional and Conventional Artificial Neural Networks for Laser-Induced Breakdown Spectroscopy Quantitative Analysis.

Applied spectroscopy Jun 11, 2022
The introduction of "deep learning" algorithms for feature identification in digital imaging has paved the way for artificial intelligence applications that up to a decade ago were considered technologically impossible to achieve, from the developmen...
Neural Networks, Computer Artificial Intelligence Algorithms Spectrum Analysis
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Theoretical Framework to Predict Generalized Contrast-to-Noise Ratios of Photoacoustic Images With Applications to Computer Vision.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control May 26, 2022
The successful integration of computer vision, robotic actuation, and photoacoustic imaging to find and follow targets of interest during surgical and interventional procedures requires accurate photoacoustic target detectability. This detectability ...
Computers Image Processing, Computer-Assisted Robotics Spectrum Analysis Signal-To-Noise Ratio Phantoms, Imaging Photoacoustic Techniques
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High-Speed Ultraviolet Photoacoustic Microscopy for Histological Imaging with Virtual-Staining assisted by Deep Learning.

Journal of visualized experiments : JoVE Apr 28, 2022
Surgical margin analysis (SMA), an essential procedure to confirm the complete excision of cancerous tissue in tumor resection surgery, requires intraoperative diagnostic tools to avoid repeated surgeries due to a positive surgical margin. Recently, ...
Animals Deep Learning Mice Staining and Labeling Microscopy Spectrum Analysis Photoacoustic Techniques
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Beyond Woodward-Fieser Rules: Design Principles of Property-Oriented Chromophores Based on Explainable Deep Learning Optical Spectroscopy.

Journal of chemical information and modeling Apr 27, 2022
An adequate understanding of molecular structure-property relationships is important for developing new molecules with desired properties. Although deep learning optical spectroscopy (DLOS) has been successfully applied to predict the optical and pho...
Deep Learning Molecular Structure Solvents Spectrum Analysis Chemical Phenomena
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Machine learning recognition of protein secondary structures based on two-dimensional spectroscopic descriptors.

Proceedings of the National Academy of Sciences of the United States of America Apr 27, 2022
Protein secondary structure discrimination is crucial for understanding their biological function. It is not generally possible to invert spectroscopic data to yield the structure. We present a machine learning protocol which uses two-dimensional UV ...
Neural Networks, Computer Machine Learning Proteins Spectrum Analysis
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Composition analysis of ceramic raw materials using laser-induced breakdown spectroscopy and autoencoder neural network.

Analytical methods : advancing methods and applications Mar 31, 2022
In the ceramic production process, the content of Si, Al, Mg, Fe, Ti and other elements in the ceramic raw materials has an important impact on the quality of the ceramic products. Exploring a method that can quickly and accurately analyze the conten...
Neural Networks, Computer Spectrum Analysis Lasers Ceramics
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An analysis framework for clustering algorithm selection with applications to spectroscopy.

PloS one Mar 31, 2022
Cluster analysis is a valuable unsupervised machine learning technique that is applied in a multitude of domains to identify similarities or clusters in unlabelled data. However, its performance is dependent of the characteristics of the data it is b...
Machine Learning Algorithms Cluster Analysis Unsupervised Machine Learning Spectrum Analysis
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A fast multi-source information fusion strategy based on deep learning for species identification of boletes.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Mar 10, 2022
Wild mushroom market is an important economic source of Yunnan province in China, and its wild mushroom resources are also valuable wealth in the world. This work will put forward a method of species identification and optimize the method in order to...
Deep Learning China Agaricales Spectrum Analysis
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Gaussian process regression for absorption spectra analysis of molecular dimers.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Mar 1, 2022
A common task is the determination of system parameters from spectroscopy, where one compares the experimental spectrum with calculated spectra, that depend on the desired parameters. Here we discuss an approach based on a machine learning technique,...
Machine Learning Spectrum Analysis Normal Distribution
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Reflectance spectroscopy and machine learning as a tool for the categorization of twin species based on the example of the Diachrysia genus.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Feb 17, 2022
In our work we used noninvasive point reflectance spectroscopy in the range from 400 to 2100 nm coupled with machine learning to study scales on the brown and golden iridescent areas on the dorsal side of the forewing of Diachrysia chrysitis and D. s...
Machine Learning Animals Spectrum Analysis Moths
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