UID:
almahu_9949434975102882
Format:
1 online resource (various pagings) :
,
illustrations (some color).
ISBN:
9780750339278
,
9780750339261
Series Statement:
IOP series in spectroscopic methods and applications
Content:
This collection highlights gemstone identification and analysis using spectroscopic techniques. It also includes the exciting applications of artificial intelligence and machine learning technologies that are being developed and used to enhance the efficiency of identification and analysis techniques.
Note:
"Version: 20221201"--Title page verso.
,
1. Laser-induced breakdown spectroscopy for gemological testing / Francesco Poggialini, Beatrice Campanella, Stefano Legnaioli, Simona Raneri and Vincenzo Palleschi -- 2. Raman spectroscopy for the non-destructive analysis of gemstones / Danilo Bersani, Laura Fornasini, Peter Vandenabeele and Anastasia Rousaki -- 3. Application of Fourier-transformed infrared spectroscopy and machine learning algorithm for gem identification / Pimthong Thongnopkun, Kanet Wongravee, Prompong Pienpinijtham and Aumaparn Phlayrahan -- 4. A ruby stone grading inspection using an optical tomography system / Syarfa Najihah Raisin, Juliza Jamaludin and Fatinah Mohd Rahalim -- 5. Trace elements and big data application to gemology by x-ray fluorescence / Yujie Gao, Moqing Lin, Xu Li and Xueying Sun.
,
Also available in print.
,
Mode of access: World Wide Web.
,
System requirements: Adobe Acrobat Reader, EPUB reader, or Kindle reader.
Additional Edition:
Print version: ISBN 9780750339254
Additional Edition:
ISBN 9780750339285
Language:
English
DOI:
10.1088/978-0-7503-3927-8
URL:
https://iopscience.iop.org/book/edit/978-0-7503-3927-8
