On the public citation graph

Spatial–spectral transformer regression improves soil organic carbon estimation from fused VNIR–SWIR hyperspectral imaging

https://doi.org/10.2139/ssrn.7358018
0 signed · 23 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1007/s10712-019-09524-0openalex-snapshot
Imaging Spectroscopy for Soil Mapping and Monitoring
inferredcites →https://doi.org/10.1007/s42729-025-02333-yopenalex-snapshot
SpatialFormer: A Model to Estimate Soil Organic Carbon Content Using Spectral and Spatial Information
inferredcites →https://doi.org/10.1016/j.catena.2018.04.013openalex-snapshot
Soil organic carbon stocks and their determining factors in the Dano catchment (Southwest Burkina Faso)
inferredcites →https://doi.org/10.1016/j.geoderma.2019.06.016openalex-snapshot
Convolutional neural network for simultaneous prediction of several soil properties using visible/near-infrared, mid-infrared, and their combined spectra
inferredcites →https://doi.org/10.1016/j.jai.2023.09.001openalex-snapshot
Non-intrusive soil carbon content quantification methods using machine learning algorithms: A comparison of microwave and millimeter wave radar sensors
inferredcites →https://doi.org/10.1016/j.still.2021.105284openalex-snapshot
Fusion of visible-to-near-infrared and mid-infrared spectroscopy to estimate soil organic carbon
inferredcites →https://doi.org/10.1017/s0021900200047604openalex-snapshot
Soft Modelling by Latent Variables: The Non-Linear Iterative Partial Least Squares (NIPALS) Approach
inferredcites →https://doi.org/10.1038/s42256-020-00257-zopenalex-snapshot
Shortcut learning in deep neural networks
inferredcites →https://doi.org/10.1038/s43586-026-00470-xopenalex-snapshot
Hyperspectral imaging
inferredcites →https://doi.org/10.1039/c4cs00062eopenalex-snapshot
Near-infrared spectroscopy and hyperspectral imaging: non-destructive analysis of biological materials
inferredcites →https://doi.org/10.1071/sr14246openalex-snapshot
Impact of soil organic matter on soil properties—a review with emphasis on Australian soils
inferredcites →https://doi.org/10.1109/lgrs.2022.3201266openalex-snapshot
Attention-Based CNN Ensemble for Soil Organic Carbon Content Estimation With Spectral Data
inferredcites →https://doi.org/10.1109/tgrs.2021.3130716openalex-snapshot
SpectralFormer: Rethinking Hyperspectral Image Classification With Transformers
inferredcites →https://doi.org/10.1109/tgrs.2022.3221534openalex-snapshot
Perceiving Spectral Variation: Unsupervised Spectrum Motion Feature Learning for Hyperspectral Image Classification
inferredcites →https://doi.org/10.1109/tgrs.2024.3446042openalex-snapshot
SSL-SoilNet: A Hybrid Transformer-Based Framework With Self-Supervised Learning for Large-Scale Soil Organic Carbon Prediction
inferredcites →https://doi.org/10.1111/ejss.13481openalex-snapshot
In‐field soil spectroscopy in Vis–NIR range for fast and reliable soil analysis: A review
inferredcites →https://doi.org/10.1255/jnirs.1003openalex-snapshot
Hyperspectral Imaging: A Review of Best Practice, Performance and Pitfalls for in-line and on-line Applications
inferredcites →https://doi.org/10.1609/aaai.v37i1.25221openalex-snapshot
Spatial-Spectral Transformer for Hyperspectral Image Denoising
inferredcites →https://doi.org/10.2136/sssaj2001.652480xopenalex-snapshot
Near‐Infrared Reflectance Spectroscopy–Principal Components Regression Analyses of Soil Properties
inferredcites →https://doi.org/10.3390/app12010174openalex-snapshot
ODPA-CNN: One Dimensional Parallel Atrous Convolution Neural Network for Band-Selective Hyperspectral Image Classification
inferredcites →https://doi.org/10.4236/ars.2019.84007openalex-snapshot
Hyperspectral Analysis for a Robust Assessment of Soil Properties Using Adapted PLSR Method
inferredcites →https://doi.org/10.5194/soil-6-565-2020openalex-snapshot
The influence of training sample size on the accuracy of deep learning models for the prediction of soil properties with near-infrared spectroscopy data
inferredcites →https://doi.org/10.7717/peerj.13740openalex-snapshot
Soil carbon sequestration potential in global croplands
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.