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Identification

Personal identification

Full name
VERONIQUE IMPERATRIZ MEDEIROS GOMES

Citation names

  • Gomes, Véronique

Author identifiers

Ciência ID
091E-BCE4-873B
ORCID iD
0000-0002-1281-4760
Education
Degree Classification
2009/03/16
Concluded
 Engenharia Química (Mestrado integrado)
Major in Biossistemas
Universidade de Coimbra Faculdade de Ciencias e Tecnologia, Portugal
"Técnicas de Análise de Genoma" (THESIS/DISSERTATION)
Projects

Grant

Designation Funders
2016 - 2016 INTERACT - Integrative Research in Environment, Agro-Chains and Technology
NORTE-01-0145-FEDER-000017
Research Fellow
Concluded
2012/04 - 2015/06 Hyper - Application of Hyperspectral Imaging and Neural Networks to Viticulture
Provided by PTCRIS: 121056
 Governo da República Portuguesa Ministério da Ciência Tecnologia e Ensino Superior
2014 - 2015 ENOEXEL, From Vineyard to Wine: Targeting Grape and Wine Excellency
NORTE-01-0124-FEDER-000033
Research Fellow
Concluded
2010/06 - 2013/11 Development of an unified framework for the integrated multivariate and multiscale monitoring of profiles
Provided by PTCRIS: 108597
 Governo da República Portuguesa Ministério da Ciência Tecnologia e Ensino Superior
Outputs

Publications

Book
  1. Fernandes, A.; Gomes, V.; Melo-Pinto, P.. A review of the application to emergent subfields in viticulture of local reflectance and interactance spectroscopy combined with soft computing and multivariate analysis. 2018.
    10.1007/978-3-319-62359-7_5
Book chapter
  1. Moita, Raquel D.; Gomes, Véronique M.; Saraiva, Pedro M.; Reis, Marco S.. "An Extended Comparative Study of Two- and Three-Way Methodologies for the On-line Monitoring of Batch Processes". edited by Jirí Jaromír Klemeš, Petar Sabev Varbanov; Peng Yen Liew, 517-522. 2014.
    http://dx.doi.org/10.1016/B978-0-444-63456-6.50087-9
  2. Moita, R.D.; Gomes, V.M.; Saraiva, P.M.; Reis, M.S.. "An Extended Comparative Study of Two- and Three-Way Methodologies for the On-line Monitoring of Batch Processes". 517-522. 2014.
    10.1016/B978-0-444-63456-6.50087-9
Conference paper
  1. Gomes, Véronique. "Towards robust Machine Learning models for grape ripeness assessment". 2021.
    10.1109/jcsse53117.2021.9493822
  2. Lucca, G.; Antonio Sanz, J.; Bustince, H.; Dimuro, G.P.; Gomes, V.; Constantino Madureira, R.C.; Melo-Pinto, P.. "Applying aggregation and pre-aggregation functions in the classification of grape berries". 2018.
    10.1109/Fuzz-Ieee.2018.8491536
  3. Rato, T.; Rendall, R.; Gomes, V.; Chin, S.-T.; Chiang, L.H.; Saraiva, P.; Reis, M.. "An extensive comparison study of batch process monitoring approaches". 2015.
  4. Gomes, V. M.; Fernandes, A. M.; Faia, A.; Melo-Pinto, P.. "Determination of sugar content in whole Port Wine grape berries combining hyperspectral imaging with neural networks methodologies". 2014.
    10.1109/CIES.2014.7011850
  5. Veronique M. Gomes; Armando M. Fernandes; Arlete Faia; Pedro Melo-Pinto. "Determination of sugar content in whole Port Wine grape berries combining hyperspectral imaging with neural networks methodologies". 2014.
    10.1109/cies.2014.7011850
Journal article
  1. Véronique Gomes; Ricardo Rendall; Marco Seabra Reis; Ana Mendes-Ferreira; Pedro Melo-Pinto. "Determination of Sugar, pH, and Anthocyanin Contents in Port Wine Grape Berries through Hyperspectral Imaging: An Extensive Comparison of Linear and Non-Linear Predictive Methods". Applied Sciences (2021): https://doi.org/10.3390/app112110319.
    10.3390/app112110319
  2. Véronique Gomes; Marco S. Reis; Francisco Rovira-Más; Ana Mendes-Ferreira; Pedro Melo-Pinto. "Prediction of Sugar Content in Port Wine Vintage Grapes Using Machine Learning and Hyperspectral Imaging". Processes (2021): https://www.mdpi.com/2227-9717/9/7/1241.
    10.3390/pr9071241
  3. Gomes, Véronique. "Application of Hyperspectral Imaging and Deep Learning for Robust Prediction of Sugar and pH Levels in Wine Grape Berries". Sensors 21 10 (2021): 3459-3459. http://dx.doi.org/10.3390/s21103459.
    10.3390/s21103459
  4. Tiago J. Rato; Ricardo Rendall; Veronique Gomes; Pedro M. Saraiva; Marco S. Reis. "A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part II—Assessing Detection Speed". Industrial & Engineering Chemistry Research 57 15 (2018): 5338-5350. https://doi.org/10.1021%2Facs.iecr.7b04911.
    10.1021/acs.iecr.7b04911
  5. Rui Silva; Véronique Gomes; Arlete Mendes-Faia; Pedro Melo-Pinto. "Using Support Vector Regression and Hyperspectral Imaging for the Prediction of Oenological Parameters on Different Vintages and Varieties of Wine Grape Berries". Remote Sensing 10 2 (2018): 312-312. https://doi.org/10.3390%2Frs10020312.
    10.3390/rs10020312
  6. Véronique Gomes; Armando Fernandes; Paula Martins-Lopes; Leonor Pereira; Arlete Mendes Faia; Pedro Melo-Pinto. "Characterization of neural network generalization in the determination of pH and anthocyanin content of wine grape in new vintages and varieties". Food Chemistry 218 (2017): 40-46. https://doi.org/10.1016/j.foodchem.2016.09.024.
    10.1016/j.foodchem.2016.09.024
  7. Gomes, V.M.; Fernandes, A.M.; Faia, A.; Melo-Pinto, P.. "Comparison of different approaches for the prediction of sugar content in new vintages of whole Port wine grape berries using hyperspectral imaging". Computers and Electronics in Agriculture 140 (2017): 244-254. http://www.scopus.com/inward/record.url?eid=2-s2.0-85020856321&partnerID=MN8TOARS.
    10.1016/j.compag.2017.06.009
  8. Rato, Tiago J.; Rendall, Ricardo; Gomes, Veronique; Chin, Swee-Teng; Chiang, Leo H.; Saraiva, Pedro M.; Reis, Marco S.. "A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part I—Assessing Detection Strength". Industrial & Engineering Chemistry Research (2016):
    10.1021/acs.iecr.5b04851
  9. Gomes, V.; Fernandes, A.; Faia, A.; Pinto, P. M.; Destech Publicat, Inc. "A Comparison of Neural Networks and Partial Least Squares for Estimation of Sugar Content in Wine Grape Berries Using Hyperspectral Imaging". International Conference on Computer Science and Environmental Engineering (Csee 2015) (2015): 1052-1059. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000361831900139&KeyUID=WOS:000361831900139.
  10. Gomes, Véronique M.; Pereira, Ana C.; Saraiva, Pedro M.; Reis, Marco S.. "Development of Generalized Platforms for the Analysis of Complex Datasets". Quality and Reliability Engineering International 28 5 (2012): 508-523. http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=ORCID&SrcApp=OrcidOrg&DestLinkType=FullRecord&DestApp=WOS_CPL&KeyUT=WOS:000306899000004&KeyUID=WOS:000306899000004.
    10.1002/qre.1443
Activities

Oral presentation

Presentation title Event name
Host (Event location)
2019/12/13 Wine grape ripeness assessment using HIS and Artificial Intelligence Digital Agro-Food & Floresty (r)evolution
UTAD (Vila Real, Portugal)
2019/11/20 Wine grape quality assessment using hyperspectral imaging bits.utad2019
UTAD (Vila Real, Portugal)
2019/05/22 Wine grape ripeness assessment using Hyperspectral imaging Enoforum 2019
(Vicenza, Italy)
2018/11/08 Wine grape quality assessment using hyperspectral imaging: A predictive analytics comparison framework International Congress on Grapevine and Wine Science
Instituto de las Ciencias de la Vid y del Vino (Logroño, Spain)
2016/05/27 A systematic evaluation and comparison of predictions methods for assessing grapes' ripeness based on intelligent spectral image systems CITAB's Science Release
CITAB (Vila Real, Portugal)
2015 A comparison of neural networks and partial least squares for estimation of sugar content in wine grape berries using hyperspectral imaging AECA2015 - International Conference on agricultural Engineering and Computer Application
AECA2015 (Hong Kong, China)
2014 Determination of sugar content in whole Port Wine grape berries combining hyperspectral imaging with neural networks methodologies IEEE SSCI 2014 – IEEE Symposium Series on Computational Intelligence
IEEE (Orlando, United States)
2014 Comparison of different approaches for the prediction of sugar content in whole Port wine grape berries using hyperspectral imaging ENBIS-14 – 14th Annual ENBIS Conference
ENBIS (Linz, Austria)
2014 An Extended Comparative Study of Two- and Three-Way Methodologies for the On-line Monitoring of Batch Processes 24th European Symposium on Computer Aided Chemical Engineering
(Budapest, Hungary)
2013 A Comparison of two and Three-way Methodologies for On-line Batch Process Monitoring ENBIS13 – 13th Annual ENBIS Conference
(Ankara, Turkey)
2011 A Comparison of Two-way and Three-way Methodologies for the Prediction of Wine Age ENBIS-11 – 11th Annual ENBIS Conference
(Coimbra, Portugal)
2011 Towards a systematization of profile analysis methods as a basis for the development of flexible and generalized data analysis frameworks ENBIS-11 – 11th Annual ENBIS Conference
(Coimbra, Portugal)
2011 A Comparison Study of Several Multiway Calibration Methodologies CHEMPOR 2011 – 11th International Chemical and Biological Engineering Conference
(Lisboa, Portugal)
Distinctions

Award

2017 Best Project Award at 5th edition of VISUM – a Summer School on Vision Understanding and Machine Intelligence

Other distinction

2019 Top 5 best works of the 4th SIVE Award “International Research for Development” - OENOPPIA Award 2019