Работы, на которые ссылается эта работа

Работ: 18

Работа: A concentration-invariant FTIR chemometric workflow for closed-library compound identification with peak-sparse representation and machine-learning classification

1. Smoothing and Differentiation of Data by Simplified Least Squares Procedures.

   Abraham Savitzky, Marcel J. E. Golay

   Статья1964Цитирований: 11

   ABIABI:AkademIndex/openalex/2026.other.295946

2. Baseline correction using asymmetrically reweighted penalized least squares smoothing

   Sung‐June Baek, Aaron Park, Young‐Jin Ahn +1

   Статья2014Цитирований: 2

   ABIABI:AkademIndex/openalex/2026.other.664120

3. Machine Learning-Empowered FTIR Spectroscopy Serum Analysis Stratifies Healthy, Allergic, and SIT-Treated Mice and Humans

   Elke Korb, Murat Bağcıoğlu, Erika Garner‐Spitzer +3

   Статья2020Цитирований: 2

   ABIABI:AkademIndex/openalex/2026.other.664122

4. A guide to good practice in chemometric methods for vibrational spectroscopy, electrochemistry, and hyphenated mass spectrometry

   Manuel David Peris‐Díaz, Artur Krężel

   Статья2020Цитирований: 2

   ABIABI:AkademIndex/openalex/2026.other.664123

5. Insights on the role of chemometrics and vibrational spectroscopy in fruit metabolite analysis

   Yasmina Sultanbawa, Heather E. Smyth, Khai N. Truong +2

   Обзорная статья2021Цитирований: 2

   ABIABI:AkademIndex/openalex/2026.other.664124

6. Recent advances of vibrational spectroscopy and chemometrics for forensic biological analysis

   Ayari Takamura, Takeaki Ozawa

   Обзорная статья2021Цитирований: 2

   ABIABI:AkademIndex/openalex/2026.other.664125

7. ATR-FTIR Spectroscopy Combined with Chemometric Methods for the Classification of Polyethylene Residues Containing Different Contaminants

   Daniel José da Silva, Hélio Wiebeck

   Статья2022Цитирований: 2

   ABIABI:AkademIndex/openalex/2026.other.664126

8. Machine Learning Systems Detecting Illicit Drugs Based on Their ATR-FTIR Spectra

   Iulia-Florentina Darie, Stefan R. Anton, Mirela Praisler

   Статья2023Цитирований: 2

   ABIABI:AkademIndex/openalex/2026.other.664127

9. Process Analytical Technology (PAT) Model Lifecycle Management

   Larry McDermott

   Статья2023Цитирований: 2

   ABIABI:AkademIndex/openalex/2026.other.664128

10. A Review of Machine Learning Methods Recently Applied to FTIR Spectroscopy Data for the Analysis of Human Blood Cells

    Ahmed Fadlelmoula, Susana O. Catarino, Graça Minas +1

    Обзорная статья2023Цитирований: 2

    ABIABI:AkademIndex/openalex/2026.other.664129

11. ATR-FTIR combined with machine learning for the fast non-targeted screening of new psychoactive substances

    Yu Du, Zhendong Hua, Cuimei Liu +3

    Статья2023Цитирований: 2

    ABIABI:AkademIndex/openalex/2026.other.664130

12. Spectraformer: deep learning model for grain spectral qualitative analysis based on transformer structure

    Zhuo Chen, Ri-gui Zhou, Pengju Ren

    Статья2024Цитирований: 2

    ABIABI:AkademIndex/openalex/2026.other.664131

13. A Review of the Latest Research Applications Using FT-IR Spectroscopy

    Jerome Workman

    Обзорная статья2024Цитирований: 2

    ABIABI:AkademIndex/openalex/2026.other.664132

14. FTIR spectroscopy combined with machine learning for the classification of Mediterranean honey based on origin

    Dafni Dimakopoulou‐Papazoglou, Salud Serrano, Inmaculada Rodríguez +3

    Статья2025Цитирований: 2

    ABIABI:AkademIndex/openalex/2026.other.664133

15. Versatile machine learning algorithms for FTIR spectroscopy: differentiating crosslinked and non-crosslinked gelatin samples

    Juliana Rincón‐López, Eliana Álvarez-Valdés, Daniela Velez-Arango +6

    Статья2025Цитирований: 2

    ABIABI:AkademIndex/openalex/2026.other.664134

16. Без названия

    ДругоеЦитирований: 1

    ABIABI:AkademIndex/openalex/2026.other.863310

17. Без названия

    ДругоеЦитирований: 1

    ABIABI:AkademIndex/openalex/2026.other.863311

18. Без названия

    ДругоеЦитирований: 1

    ABIABI:AkademIndex/openalex/2026.other.863312