arXiv (OAI Expanded)
open access
Decision Tree and K-Means Analysis of Raman Spectra for Edible Oils: A Physics-Informed AI Approach
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Decision Tree and K-Means Analysis of Raman Spectra for Edible Oils: A Physics-Informed AI Approach#659012
- Raman analysis of black carbon using artificial neural networks for emission source classification#140159
- Raman analysis of black carbon using artificial neural networks for emission source classification.#136123
- Multi-scale fusion SDAM-net empowered by physics-informed conditional spectral augmentation enabling spectral feature assignment for the concurrent detection of nitrogen and sulfur in ship fuel oil.#613380
- Cross-material catalyst discovery via deep learning#631894
Record · ID 656876
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive