Data-mining Based Expert Platform for the Spectral Inspection
Hai-Jun Tian, Yang Tu, Yan-Xia Zhang, Yong-Heng Zhao, Guo-Hong Lei,, Bo-Liang He, Chen-Zhou Cui, Xue-Lei Chen
TL;DR
This paper introduces a multi-layer data-mining platform designed to assist experts in inspecting large volumes of low SNR spectra from sky surveys, enhancing spectral data management and analysis.
Contribution
It presents a novel multi-layer platform architecture that integrates data-mining techniques for spectral inspection, inspired by GalaxyZoo and VO standards.
Findings
Platform effectively manages spectral data
Assists experts in inspecting low SNR spectra
Preliminary results show promising performance
Abstract
We propose and preliminarily implement a data-mining based platform to assist experts to inspect the increasing amount of spectra with low signal to noise ratio (SNR) generated by large sky surveys. The platform includes three layers: data-mining layer, data-node layer and expert layer. It is similar to the GalaxyZoo project and VO-compatible. The preliminary experiment suggests that this platform can play an effective role in managing the spectra and assisting the experts to inspect a large number of spectra with low SNR.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAstronomical Observations and Instrumentation · Infrared Target Detection Methodologies · Optical Wireless Communication Technologies