Yunsong Liu

Oct 18, 2024 | spectroscopyonline.com | Yitao Chen |Xinyi Wang |Sufang Zhou |Yunsong Liu |Ding Zhang |Yaoxinyu Yang

To identify the geographical origin of millet accurately, 36 samples of Guangling millet, Qinzhouhuang millet, Liuseng millet, Qiananhuang millet, and 33 samples of Yuzhou millet were collected. Mid-infrared (mid-IR) spectra of all the samples were obtained. Denoising, standard normal variate (SNV), multiplicative scatter correction (MSC), and normalization were carried out to preprocess the data.

Oct 4, 2024 | arxiv.org | Yunsong Liu |Agam Shah |Sudheer Chava |Mingxiao Song

arXiv:2410.03099 (cs) View PDF HTML (experimental) Comments: Subjects: Computation and Language (cs.CL) Cite as: arXiv:2410.03099 [cs.CL] (or arXiv:2410.03099v1 [cs.CL] for this version) https://doi.org/10.48550/arXiv.2410.03099 Submission history From: Agam Shah [ view email] [v1] Fri, 4 Oct 2024 02:49:18 UTC (5,844 KB) Bibliographic Tools Bibliographic Explorer Toggle Bibliographic Explorer () Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart...

May 25, 2023 | arxiv.org | Yunsong Liu |Agam Shah |Sudheer Chava

[Submitted on 25 May 2023 (v1), last revised 2 Aug 2023 (this version, v2)] Title:Abnormal Trading Detection in the NFT Market Download a PDF of the paper titled Abnormal Trading Detection in the NFT Market, by Mingxiao Song and Yunsong Liu and Agam Shah and Sudheer Chava Download PDF Abstract: The Non-Fungible-Token (NFT) market has experienced explosive growth inrecent years.