arXiv (OAI Expanded)
open access
Multiple Linear Regression-Enhanced RGB-based Luminescence Thermometry for High-sensitivity Thermal Readout
The practical implementation of phosphors for luminescence-based thermal sensing and imaging requires simple, user-friendly approaches that enable convenient and sensitive temperature readout. To the best of our knowledge, this is the first demonstration of combining RGB-based thermal imaging using
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
- Synthetic Thermal Image Generation for Real-Time Animal Detection Under Low-Visibility Conditions#1117656
- Unravelling radiative energy transfer in solid-state lighting#955323
- Characterising and exploiting sensitisation processes in luminescence thermometry / Linda Dalipi ; Gutachter: Benoît Fond, Frank Beyrau, Hélène Serier-Brault#1145579
- Replication Data for: Blue Light Enhances Background Current and Dopamine Sensitivity of Carbon-Fiber Microelectrodes During Fast-Scan Cyclic Voltammetry#1028201
- Mechanistic insights into electrochemiluminescence: fueling advances in bioanalysis and imaging.#636433
Record · ID 1084986
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