On the public citation graph

Online rapid detection of polyester content blended fabrics using hyperspectral imaging and a stratified prediction model

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/col.22738openalex-extracted

Evaluation and consistency calibration of hyperspectral imaging system based on liquid crystal tunable filter for fabric color measurement

inferredcites →https://doi.org/10.1007/s10311-024-01726-2openalex-extracted

Textile production by additive manufacturing and textile waste recycling: a review

inferredcites →https://doi.org/10.1007/s11356-021-16301-3openalex-extracted

Predicting evaporation with optimized artificial neural network using multi-objective salp swarm algorithm

inferredcites →https://doi.org/10.1016/j.ecoinf.2025.103192openalex-extracted

ResHAN-GAM: A novel model for the inversion and prediction of soil organic matter content

inferredcites →https://doi.org/10.1016/j.jfca.2025.107815openalex-extracted

Rapid detection of mutton freshness grades and TVB-N using hyperspectral imaging with optimized machine learning and lightweight deep learning models

inferredcites →https://doi.org/10.1016/j.mran.2024.100295openalex-extracted

Assessment of food safety risk using machine learning-assisted hyperspectral imaging: Classification of fungal contamination levels in rice grain

inferredcites →https://doi.org/10.1016/j.optlaseng.2021.106632openalex-extracted

Spectral shift correction and adaptive band selection for multispectral imaging

inferredcites →https://doi.org/10.1016/j.pce.2024.103605openalex-extracted

Estimating aboveground biomass of urban trees based on ICESat-2 LiDAR and Zhuhai-1 hyperspectral data

inferredcites →https://doi.org/10.1016/j.resconrec.2020.105007openalex-extracted

Machine vision estimates the polyester content in recyclable waste textiles

inferredcites →https://doi.org/10.1016/j.saa.2025.126410openalex-extracted

Rapid and non-destructive detection of wood density based on NIR hyperspectral imaging technology and moisture correction methods

inferredcites →https://doi.org/10.1016/j.saa.2025.126542openalex-extracted

Feasibility assessment on the use of near infrared hyperspectral imaging for the screening of vitamin C content and total soluble solids in strawberries

inferredcites →https://doi.org/10.1080/10106049.2025.2476599openalex-extracted

A synergistic PCA and C-A fractal approach for high-precision extraction of mineral alteration anomalies from ASTER remote sensing data

inferredcites →https://doi.org/10.1080/10298436.2025.2468366openalex-extracted

A reliable approach for classifying metakaolin content of high-Performance concrete via machine learning algorithm

inferredcites →https://doi.org/10.1109/34.141557openalex-extracted

An analysis of camera noise

inferredcites →https://doi.org/10.1109/jsen.2023.3238673openalex-extracted

Estimation of Camera’s Noise by Uniform Target Segmentation

inferredcites →https://doi.org/10.1117/12.328561openalex-extracted

Experimental and theoretical characterization of noise in a streak camera

inferredcites →https://doi.org/10.1364/ao.54.003687openalex-extracted

Wavelength-dependent spatial correction and spectral calibration of a liquid crystal tunable filter imaging system

inferredcites →https://doi.org/10.1366/000370206777412194openalex-extracted

Quantitative Analysis of Cotton—Polyester Textile Blends from Near-Infrared Spectra

inferredcites →https://doi.org/10.1366/0003702963905655openalex-extracted

Liquid Crystal Tunable Filter Raman Chemical Imaging

inferredcites →https://doi.org/10.1595/205651319x15574756736831openalex-extracted

Closed-Loop Recycling of Polymers Using Solvents

inferredcites →https://doi.org/10.3389/fenrg.2022.905155openalex-extracted

A Short-Term Wind Power Forecast Method via XGBoost Hyper-Parameters Optimization

inferredcites →https://doi.org/10.3390/molecules26030749openalex-extracted

A Review of the Discriminant Analysis Methods for Food Quality Based on Near-Infrared Spectroscopy and Pattern Recognition

inferredcites →https://doi.org/10.3390/recycling10040152openalex-extracted

Quantifying Cotton Content in Post-Consumer Polyester/Cotton Blend Textiles via NIR Spectroscopy: Current Attainable Outcomes and Challenges in Practice

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.3390/pr14060964openalex-snapshot

FTIR-Based Machine Learning Identification of Virgin and Recycled Polyester for Textile Recycling in Industry 4.0

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