AIMC Topic: Least-Squares Analysis

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A machine learning approach fusing multisource spectral data for prediction of floral origins and taste components of Apis cerana honey.

Food research international (Ottawa, Ont.) Feb 25, 2025
This study explores the use of near-infrared (NIR), mid-infrared (MIR), and Raman spectral fusion for the rapid prediction of floral origins and main taste components in Apis cerana (A. cerana) honey. Feature-level fusion with the partial least squar...
Honey Spectrum Analysis, Raman Taste Least-Squares Analysis Flowers Amino Acids Bees Machine Learning Sugars Animals Spectroscopy, Near-Infrared
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Using visible and NIR hyperspectral imaging and machine learning for nondestructive detection of nutrient contents in sorghum.

Scientific reports Feb 19, 2025
Nondestructive, rapid, and accurate detection of nutritional compositions in sorghum is crucial for agricultural and food industries. In our study, the crude protein, tannin, and crude fat contents of sorghum variety samples were taken as the researc...
Machine Learning Algorithms Nutritive Value Sorghum Hyperspectral Imaging Tannins Spectroscopy, Near-Infrared Least-Squares Analysis Nutrients
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Unveiling the potential of Brachiaria ruziziensis: Comparative analysis of multivariate and machine learning models for biomass and NPK prediction using Vis-NIR-SWIR spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Feb 18, 2025
This study investigated the development and validation of predictive models for estimating foliar nitrogen (N), phosphorus (P), and potassium (K) contents, along with shoot dry mass (SDM) of Brachiaria ruziziensis L. The approach utilized Vis-NIR-SWI...
Plant Leaves Least-Squares Analysis Nitrogen Biomass Spectroscopy, Near-Infrared Support Vector Machine Brachiaria Potassium Phosphorus Multivariate Analysis Machine Learning
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Exploring the impact of lenticels on the detection of soluble solids content in apples and pears using hyperspectral imaging and one-dimensional convolutional neural networks.

Food research international (Ottawa, Ont.) Feb 7, 2025
In this work, the effect of lenticels on the predictive performance of apple and pear soluble solids content (SSC) models developed based on hyperspectral imaging (HSI) at 380-1010 nm was investigated for the first time. Variations in the spectral pr...
Fruit Hyperspectral Imaging Calibration Malus Neural Networks, Computer Principal Component Analysis Pyrus Algorithms Least-Squares Analysis Discriminant Analysis Convolutional Neural Networks
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Using near-infrared hyperspectral imaging combined with machine learning to predict the components and the origin of Radix Paeoniae Rubra.

Analytical methods : advancing methods and applications Feb 6, 2025
The efficacy and safety of drugs are closely related to the geographical origin and quality of the raw materials. This study focuses on using near-infrared hyperspectral imaging (NIR-HSI) combined with machine learning algorithms to construct content...
Spectroscopy, Near-Infrared Support Vector Machine Principal Component Analysis Machine Learning Algorithms Hyperspectral Imaging Monoterpenes Paeonia Drugs, Chinese Herbal Least-Squares Analysis Glucosides
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A holistic strategy for the in-depth discrimination and authentication of 16 citrus herbs and associated commercial products based on machine learning techniques and non-targeted metabolomics.

Journal of chromatography. A Feb 1, 2025
Citrus-derived raw medicinal materials are frequently used for health care, flavoring, and therapeutic purposes. However, Due to similarities in origin or appearance, citrus herbs are often misused in the market, necessitating effective differentiati...
Citrus Machine Learning Metabolomics Drugs, Chinese Herbal Least-Squares Analysis Discriminant Analysis
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A robust deep learning model for predicting green tea moisture content during fixation using near-infrared spectroscopy: Integration of multi-scale feature fusion and attention mechanisms.

Food research international (Ottawa, Ont.) Jan 30, 2025
Fixation is a critical step in green tea processing, and the moisture content of the leaves after fixation is a key indicator of the fixation quality. Near-infrared spectroscopy (NIRS)-based moisture detection technology is often applied in the tea p...
Tea Temperature Deep Learning Least-Squares Analysis Spectroscopy, Near-Infrared Water Food Handling Plant Leaves
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Cooking loss estimation of semispinalis capitis muscle of pork butt using a deep neural network on hyperspectral data.

Meat science Jan 10, 2025
This study evaluated the performance of a deep-learning-based model that predicted cooking loss in the semispinalis capitis (SC) muscle of pork butts using hyperspectral images captured 24 h postmortem. To overcome low-scale samples, 70 pork butts we...
Hydrogen-Ion Concentration Hyperspectral Imaging Cooking Red Meat Paraspinal Muscles Pork Meat Deep Learning Principal Component Analysis Least-Squares Analysis Neural Networks, Computer Animals Swine
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Enhancing prediction of major depressive disorder onset in adolescents: A machine learning approach.

Journal of psychiatric research Jan 9, 2025
Major Depressive Disorder (MDD) is a prevalent mental health condition that often begins in adolescence, with significant long-term implications. Indicated prevention programs targeting adolescents with mild symptoms have shown efficacy, yet the meth...
Adolescent Least-Squares Analysis Portugal Male Humans Depressive Disorder, Major Machine Learning Psychiatric Status Rating Scales Female
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Improved analysis of supervised learning in the RKHS with random features: Beyond least squares.

Neural networks : the official journal of the International Neural Network Society Jan 8, 2025
We consider kernel-based supervised learning using random Fourier features, focusing on its statistical error bounds and generalization properties with general loss functions. Beyond the least squares loss, existing results only demonstrate worst-cas...
Least-Squares Analysis Humans Supervised Machine Learning Neural Networks, Computer Fourier Analysis Algorithms
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