AI Medical Compendium Journal:
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy

Showing 111 to 120 of 184 articles

Probing 1D convolutional neural network adapted to near-infrared spectroscopy for efficient classification of mixed fish.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Salmon and Cod are economically significant world-class fish that have high economic value. It is difficult to accurately sort and process them by appearance during harvest and transportation. Conventional chemical detection means are time-consuming ...

Spectroscopic profiling-based geographic herb identification by neural network with random weights.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Daodi medicinal material plays an important role in traditional Chinese medicine (TCM). This study researches and validates the NNRW (neural network with random weights) model on spectroscopic profiling data for geographical origin identification. NN...

Fourier transform infrared spectrum pre-processing technique selection for detecting PYLCV-infected chilli plants.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Pre-processing is a crucial step in analyzing spectra from Fourier transform infrared (FTIR) spectroscopy because it can reduce unwanted noise and enhance system performance. Here, we present the results of pre-processing technique optimization to fa...

Blended fabric with integrated neural network based on attention mechanism qualitative identification method of near infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Near Infrared spectroscopy (NIRS) qualitative analysis technology has shown excellent development potential in the field of blend fabrics. However, the qualitative detection method based on the convolutional neural network (CNN) is difficult to accur...

Quantitative analysis of Raman spectra for glucose concentration in human blood using Gramian angular field and convolutional neural network.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
In this study, convolutional neural network based on Gramian angular field (GAF-CNN) was firstly proposed. The 1-D Raman spectral data was converted into images and used for predicting the biochemical value of blood glucose. 106 sets of blood spectru...

A fast multi-source information fusion strategy based on deep learning for species identification of boletes.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
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...

Gaussian process regression for absorption spectra analysis of molecular dimers.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
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,...

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
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...

Terahertz signal analysis and substance identification via Zernike moments.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Terahertz (THz) spectra contain chemical information, along with noise and variable backgrounds. Measurement environmental changes and spectral signal differences caused by changes in the sample state can degrade the accuracy of the calibration model...

Genetic algorithm based artificial neural network and partial least squares regression methods to predict of breakdown voltage for transformer oils samples in power industry using ATR-FTIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The current study proposes a novel analytical method for calculating the breakdown voltage (BV) of transformer oil samples considered as a significant method to assess the safe operation of power industry. Transformer oil samples can be analyzed usin...