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Tom Fearn

University College London

46H-index
381Paper Count
1.1WCitation Count
Published Papers 48
Publication Date
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Preface to the special issue: Chemometrics
errTRAC-Trends in Analytical Chemistry
IF12
err2026-04-28
err0
PREAI
errClaudia Beleites; Marina Cocchi; Stephan Seifert; Tom Fearn
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Applications, trends and challenges of emerging and innovative non-destructive spectral sensors for the assessment of food integrity issues along the entire food supply chain
errSpectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy
IF4.6
err2025-10-17
err0
PREAI
errDolores Pérez-Marín; Tom Fearn
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Bayesian optimisation for interval selection in PLS models
errChemometrics and Intelligent Laboratory Systems
IF3.8
err2025-10-10
err0
PREAI
errNicolás Hernández; Yoonsun Choi; Tom Fearn
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Multivariate Calibration of Non-Destructive Spectral Sensors with a particular focus on food applications: Validation Issues and Guidelines
errtrac trends in analytical chemistry
IF0
err2025-08-07
err0
errOAAI
errTom Fearn; Claudia Beleites; Juan Antonio Fernández Pierna; Vincent Baeten; Martin Lagerholm; Jean-Michel Roger; Anastasios Koidis
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Farinograph characteristics of wheat flour predicted by near infrared spectroscopy with an ensemble modelling method
errJOURNAL OF FOOD ENGINEERING
IF5.8
err2023-12-01
err7
errOAAI
errCui, Chenhao; Caporaso, Nicola; Chen, Jiawei; Fearn, Tom
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Optimisation of the predictive ability of NIR models to estimate nutritional parameters in elephant grass through LOCAL algorithms
errSPECTROCHIMICA ACTA PART A-MOLECULAR AND BIOMOLECULAR SPECTROSCOPY
IF4.6
err2023-01-01
err6
errOAAI
errFernandez-Cabanas, Victor M.; Perez-Marin, Dolores C.; Fearn, Tom; de Abreu, Joadil Goncalves
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Photodegradation of iron gall ink affected by oxygen, humidity and visible radiation
errDYES AND PIGMENTS
IF4.2
err2022-02-01
err7
errOAAI
errLiu, Yun; Fearn, Tom; Strlic, Matija
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Spectral sensitivity of the discoloration of Historical rag paper
errTALANTA OPEN
IF3.7
err2021-12-01
err5
errOAAI
errLiu, Yun; Fearn, Tom; Strlic, Matija
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errSave
Machine-Learning Approach for Predicting the Discharging Capacities of Doped Lithium Nickel-Cobalt-Manganese Cathode Materials in Li-Ion Batteries
errACS CENTRAL SCIENCE
IF10.4
err2021-08-20
err39
errOAAI
errWang, Guanyu; Fearn, Tom; Wang, Tengyao; Choy, Kwang-Leong
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Quantitative NIR spectroscopy for determination of degree of polymerisation of historical paper
errCHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
IF3.8
err2021-07-01
err8
errOAAI
errLiu, Yun; Fearn, Tom; Strlic, Matija
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Insight Gained from Using Machine Learning Techniques to Predict the Discharge Capacities of Doped Spinel Cathode Materials for Lithium-Ion Batteries Applications
errENERGY TECHNOLOGY
IF3.6
err2021-03-18
err9
errOAAI
errWang, Guanyu; Fearn, Tom; Wang, Tengyao; Choy, Kwang-Leong
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Probabilistic classification models for the in situ authentication of iberian pig carcasses using near infrared spectroscopy
errTALANTA
IF6.1
err2021-01-01
err20
errOAAI
errPerez-Marin, Dolores; Fearn, Tom; Riccioli, Cecilia; Pedro, Emiliano De; Garrido, Ana
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Performance comparison of sampling designs for quality and safety control of raw materials in bulk: A simulation study based on NIR spectral data and geostatistical analysis
errCHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
IF3.8
err2020-03-01
err1
errOAAI
errAdame-Siles, J. A.; Guerrero-Ginel, J. E.; Fearn, T.; Garrido-Varo, A.; Perez-Marin, D.
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Classifying with confidence using Bayes rule and kernel density estimation
errCHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
IF3.8
err2019-06-01
err9
errOAAI
errFearn, Tom; Perez-Marin, Dolores; Garrido-Varo, Ana; Emilio Guerrero-Ginel, Jose
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A system using in situ NIRS sensors for the detection of product failing to meet quality standards and the prediction of optimal postharvest shelf-life in the case of oranges kept in cold storage
errPOSTHARVEST BIOLOGY AND TECHNOLOGY
IF6.8
err2019-01-01
err13
errOAAI
errPerez-Marin, Dolores; Calero, Luis; Fearn, Tom; Torres, Irina; Garrido-Varo, Ana; Sanchez, Maria-Teresa
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Short Communication: The potential of portable near infrared spectroscopy for assuring quality and authenticity in the food chain, using Iberian hams as an example
errANIMAL
IF4.2
err2019-01-01
err17
errOAAI
errPiotrowski, C.; Garcia, R.; Garrido-Varo, A.; Perez-Marin, D.; Riccioli, C.; Fearn, T.
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Modern practical convolutional neural networks for multivariate regression: Applications to NIR calibration
errCHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
IF3.8
err2018-11-01
err237
errOAAI
errCui, Chenhao; Fearn, Tom
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errSave
Elastic scattering spectroscopy for early detection of breast cancer: partially supervised Bayesian image classification of scanned sentinel lymph nodes
errJOURNAL OF BIOMEDICAL OPTICS
IF2.9
err2018-08-21
err9
errOAAI
errZhu, Ying; Fearn, Tom; Chicken, D. Wayne; Austwick, Martin R.; Somasundaram, Santosh K.; Mosse, Charles A.; Clark, Benjamin; Bigio, Irving J.; Keshtgar, Mohammed R. S.; Bown, Stephen G.
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Hierarchical mixture of linear regressions for multivariate spectroscopic calibration An application for NIR calibration
errCHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS
IF3.8
err2018-03-01
err6
PREAI
errCui, Chenhao; Fearn, Tom
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errSave
Parent-dependent stressors and the onset of anxiety disorders in children: links with parental psychopathology
errEUROPEAN CHILD & ADOLESCENT PSYCHIATRY
IF4.9
err2017-08-08
err12
errOAAI
errAllen, Jennifer L.; Sandberg, Seija; Chhoa, Celine Y.; Fearn, Tom; Rapee, Ronald M.
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Research Directions

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Co-authors
Cooperation Journals
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Stephen E. Darby
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