On the public citation graph

FTIR spectroscopy of Ganoderma species: Exploratory chemometric and convolutional neural-network discrimination

0 signed · 25 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

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

inferredcites →https://doi.org/10.1002/cem.2977openalex-snapshot
One‐dimensional convolutional neural networks for spectroscopic signal regression
inferredcites →https://doi.org/10.1002/cem.695openalex-snapshot
Orthogonal projections to latent structures (O‐PLS)
inferredcites →https://doi.org/10.1007/s10994-022-06296-4openalex-snapshot
A theoretical distribution analysis of synthetic minority oversampling technique (SMOTE) for imbalanced learning
inferredcites →https://doi.org/10.1007/s11306-007-0099-6openalex-snapshot
Assessment of PLSDA cross validation
inferredcites →https://doi.org/10.1016/j.aca.2016.12.010openalex-snapshot
Convolutional neural networks for vibrational spectroscopic data analysis
inferredcites →https://doi.org/10.1016/j.aca.2019.01.002openalex-snapshot
DeepSpectra: An end-to-end deep learning approach for quantitative spectral analysis
inferredcites →https://doi.org/10.1016/j.carbpol.2009.05.025openalex-snapshot
Adulteration identification of some fungal polysaccharides with SEM, XRD, IR and optical rotation: A primary approach
inferredcites →https://doi.org/10.1016/j.chemolab.2021.104287openalex-snapshot
A synergistic use of chemometrics and deep learning improved the predictive performance of near-infrared spectroscopy models for dry matter prediction in mango fruit
inferredcites →https://doi.org/10.1016/j.chemolab.2021.104367openalex-snapshot
Comparison of augmentation and pre-processing for deep learning and chemometric classification of infrared spectra
inferredcites →https://doi.org/10.1016/j.ijbiomac.2019.08.003openalex-snapshot
The complete mitochondrial genomes of five important medicinal Ganoderma species: Features, evolution, and phylogeny
inferredcites →https://doi.org/10.1016/j.saa.2012.02.004openalex-snapshot
A study of Ganoderma lucidum spores by FTIR microspectroscopy
inferredcites →https://doi.org/10.1016/j.saa.2022.121350openalex-snapshot
Probing 1D convolutional neural network adapted to near-infrared spectroscopy for efficient classification of mixed fish
inferredcites →https://doi.org/10.1016/j.saa.2023.123229openalex-snapshot
Discrimination of Dioscorea species (Chinese yam) using FT-IR integrated with chemometric approach
inferredcites →https://doi.org/10.1016/j.saa.2025.127414openalex-snapshot
Qualitative and quantitative analysis of Paris polyphylla var. yunnanensis from different origin using multi-dimensions FT-MIR and NIR spectroscopy, data fusion combined with machine learning
inferredcites →https://doi.org/10.1021/ac60214a047openalex-snapshot
Smoothing and Differentiation of Data by Simplified Least Squares Procedures.
inferredcites →https://doi.org/10.1039/c8an00599kopenalex-snapshot
Partial least squares-discriminant analysis (PLS-DA) for classification of high-dimensional (HD) data: a review of contemporary practice strategies and knowledge gaps
inferredcites →https://doi.org/10.1039/d0ra07219bopenalex-snapshot
Traditional uses, chemical components and pharmacological activities of the genus Ganoderma P. Karst.: a review
inferredcites →https://doi.org/10.1186/1471-2105-7-91openalex-snapshot
Bias in error estimation when using cross-validation for model selection
inferredcites →https://doi.org/10.1366/0003702934067694openalex-snapshot
Generalized Two-Dimensional Correlation Method Applicable to Infrared, Raman, and other Types of Spectroscopy
inferredcites →https://doi.org/10.1371/journal.pone.0224365openalex-snapshot
Machine learning algorithm validation with a limited sample size
inferredcites →https://doi.org/10.1613/jair.953openalex-snapshot
SMOTE: Synthetic Minority Over-sampling Technique
inferredcites →https://doi.org/10.3390/diagnostics14161727openalex-snapshot
Exploring the Interplay of Dataset Size and Imbalance on CNN Performance in Healthcare: Using X-rays to Identify COVID-19 Patients
inferredcites →https://doi.org/10.3390/foods12071512openalex-snapshot
Exploring the Potential Medicinal Benefits of Ganoderma lucidum: From Metabolic Disorders to Coronavirus Infections
inferredcites →https://doi.org/10.3390/jof7100819openalex-snapshot
Ganoderma (Ganodermataceae, Basidiomycota) Species from the Greater Mekong Subregion
inferredcites →https://doi.org/10.5772/1150openalex-snapshot
Chemometrics in Practical Applications
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.