Quick Navigation

Overview Topics Abstract Importance Paper Tools References Reactions Discussion Publication Related

Topics

Quantum Machine Learning

Machine learning-driven spectral decomposition and pattern recognition for carbon quantum dot fluorescence sensing: From quantum confinement to multi-analyte detection

Crossref
Authors: Biju Theruvil Sayed, Zyad Shaaban, Maharshikumar B. Shukla, Sumit Sharma, Ozodbek Nematov, Ibrokhim Sapaev, M.K. Sharma, Aseel Smerat, Ahmad khayyat, Ahmad Mohebi

Year

2026

Paper ID

76777

Status

Peer-reviewed

Abstract Read

~2 min

Abstract Words

0

Citations

0

Abstract

No abstract available.

Why This Paper Matters

  • This paper contributes to the Quantum Machine Learning research area in the Quantum Articles archive.
  • It adds a 2026 reference point for readers tracking recent quantum research.

Paper Tools

Become a member to use research tools

Sign in to open papers, visit source links, share, cite, compare, copy DOI links, request category corrections, and build your reading list.

Become a member Sign in
Publisher Share Cite This Paper Copy URL Compare Copy DOI Add to Reading List Category Correction Request

References & Citation Signals

[1] DOI https://doi.org/10.1016/j.mssp.2026.111038 [2] Publisher https://doi.org/10.1016/j.mssp.2026.111038

Local Citation Graph (Related-Paper Links)

Current Paper #76777 #78828 Verifiable Sampling for Delegat... #78813 Large-Scale Benchmarking of Qua... #78775 On linearity or non-linearity i...

External citation index: OpenAlex citation signal • updated 2026-10-19 20:58:29

Community Reactions

Quick sentiment from readers on this paper.

Score: 0
Likes: 0 Dislikes: 0

Sign in to react to this paper.

Discussion & Reviews (Moderated)

Average Rating: 0.0 / 5 (0 ratings)

No written reviews yet.