Tom Fearn
researcher
Facts
8 properties- Instance of
- human
- Date of birth
- October 8, 1949
- Occupation
- statistician, mathematician
- Educated at
- University College London
- Doctoral advisor
- Dennis Lindley[4]
🏷️ Also known as
en Thomas Fearn
en Tom Fearn
🔖 Identifiers · 15
- ISNI
- 0000000081010569
- ORCID iD
- 0000-0003-2222-6601
- VIAF cluster ID
- 22226321
- Library of Congress authority ID
- n86002349
- GND ID
- 172670225
- Bibliothèque nationale de France ID
- 12399961p
- CiNii Research ID
- 1140000791574951040
- DBLP author ID
- 184/9150
- DDB person (GND) ID
- 172670225
- IdRef ID
- 159032555
- MR Author ID
- 442037
- Mathematics Genealogy Project ID
- 278206
Show all 15 identifiers +3
- NACSIS-CAT author ID
- DA04368939
- NUKAT ID
- n2017008029
- Yale LUX ID
- person/b7b9943e-991d-40ec-9c8a-8899da7be1f9
🔗 Connections
Author of 7
A note on Mahalanobis and related distance measures in WinISI and The Unscrambler,
Classifying with confidence using Bayes rule and kernel density estimation,
Comparison of partial least squares regression, least squares support vector machines, and Gaussian process regression for a near infrared calibration,
Developing a non-invasive tool to assess the impact of oxidation on the structural integrity of historic wool in Tudor tapestries,
Microscopy in combination with image analysis for characterization of fishmeal material in aquafeed,
Modern practical convolutional neural networks for multivariate regression: Applications to NIR calibration,
Probabilistic classification models for the in situ authentication of iberian pig carcasses using near infrared spectroscopy
← Authored by 7
A note on Mahalanobis and related distance measures in WinISI and The Unscrambler,
Classifying with confidence using Bayes rule and kernel density estimation,
Comparison of partial least squares regression, least squares support vector machines, and Gaussian process regression for a near infrared calibration,
Developing a non-invasive tool to assess the impact of oxidation on the structural integrity of historic wool in Tudor tapestries,
Microscopy in combination with image analysis for characterization of fishmeal material in aquafeed,
Modern practical convolutional neural networks for multivariate regression: Applications to NIR calibration,
Probabilistic classification models for the in situ authentication of iberian pig carcasses using near infrared spectroscopy
Affiliated with 1
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