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Least-Squares Analysis

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Spectroscopy and imaging technologies coupled with machine learning for the assessment of the microbiological spoilage associated to ready-to-eat leafy vegetables.

International journal of food microbiology
Based on both new and previously utilized experimental data, the present study provides a comparative assessment of sensors and machine learning approaches for evaluating the microbiological spoilage of ready-to-eat leafy vegetables (baby spinach and...

Interval-Based Least Squares for Uncertainty-Aware Learning in Human-Centric Multimedia Systems.

IEEE transactions on neural networks and learning systems
Machine learning (ML) methods are popular in several application areas of multimedia signal processing. However, most existing solutions in the said area, including the popular least squares, rely on penalizing predictions that deviate from the targe...

Impacts of multicollinearity on CAPT modalities: An heterogeneous machine learning framework for computer-assisted French phoneme pronunciation training.

PloS one
Phoneme pronunciations are usually considered as basic skills for learning a foreign language. Practicing the pronunciations in a computer-assisted way is helpful in a self-directed or long-distance learning environment. Recent researches indicate th...

A weighted twin support vector machine as a potential discriminant analysis tool and evaluation of its performance for near-infrared spectroscopic discrimination of the geographical origins of diverse agricultural products.

Talanta
A weighted twin support vector machine (wTWSVM) was proposed as a potential discriminant analysis tool and its utility was evaluated for near-infrared (NIR) spectroscopic identification of the geographical origins of 12 different agricultural product...

Spatial Prediction of COVID-19 in China Based on Machine Learning Algorithms and Geographically Weighted Regression.

Computational and mathematical methods in medicine
COVID-19 has swept through the world since December 2019 and caused a large number of patients and deaths. Spatial prediction on the spread of the epidemic is greatly important for disease control and management. In this study, we predicted the cumul...

Nature inspired computation and ensemble neural network to build a robust model for spectral data.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
UV spectrophotometry was introduced for simultaneous determination of Itraconazole (ITZ) and Secnidazole (SEZ) in their mixture without any prior separation. In this study, fourteen nature-inspired algorithms combined with partial least squares (PLS)...

Detection of heavy metal lead in lettuce leaves based on fluorescence hyperspectral technology combined with deep learning algorithm.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
The feasibility analysis of fluorescence hyperspectral imaging technology was studied for the detection of lead content in lettuce leaves. Further, Monte Carlo optimized wavelet transform stacked auto-encoders (WT-MC-SAE) was proposed for dimensional...

Study on the identification of resistance of rice blast based on near infrared spectroscopy.

Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Rice Blast is the most devastating rice disease which poses a serious threat to the safe production of rice. The most effective way to prevent rice blast is to cultivate the rice varieties that have resistance to the disease, however, traditional res...

On the Prediction of Biogas Production from Vegetables, Fruits, and Food Wastes by ANFIS- and LSSVM-Based Models.

BioMed research international
This study is aimed at modeling biodigestion systems as a function of the most influencing parameters to generate two robust algorithms on the basis of the machine learning algorithms, including adaptive network-based fuzzy inference system (ANFIS) a...

Neural networks for parameter estimation in microstructural MRI: Application to a diffusion-relaxation model of white matter.

NeuroImage
Specific features of white matter microstructure can be investigated by using biophysical models to interpret relaxation-diffusion MRI brain data. Although more intricate models have the potential to reveal more details of the tissue, they also incur...