BIO
Name: Véronique Medeiros Gomes
Aggregation: PhD Collaborator
Scopus author ID: 55324689400
Orcid ID: https://orcid.org/0000-0002-1281-4760
Ciência Vitae: 091E-BCE4-873B
Email: veroniquegomes@gmail.com
Research Tasks
Publications
Exploring the Antioxidant Potential of Phenolic Compounds from Winery By-Products by Hydroethanolic Extraction
(2023)
Exploring the Antioxidant Potential of Phenolic Compounds from Winery By-Products by Hydroethanolic Extraction
Molecules
28
(6660).
ISSN: 14203049.
doi: 10.3390/molecules28186660.
Application of hyperspectral imaging and deep learning for robust prediction of sugar and ph levels in wine grape berries
(2021)
Application of hyperspectral imaging and deep learning for robust prediction of sugar and ph levels in wine grape berries
Sensors
21
(3459).
doi: 10.3390/s21103459.
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
(2021)
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 (Switzerland)
11
(10319).
ISSN: 20763417.
doi: 10.3390/app112110319.
Prediction of sugar content in port wine vintage grapes using machine learning and hyperspectral imaging
(2021)
Prediction of sugar content in port wine vintage grapes using machine learning and hyperspectral imaging
Processes
9
(1241).
ISSN: 22279717.
doi: 10.3390/pr9071241.
Towards robust Machine Learning models for grape ripeness assessment
(2021)
Towards robust Machine Learning models for grape ripeness assessment
JCSSE 2021 - 18th International Joint Conference on Computer Science and Software Engineering: Cybernetics for Human Beings
(9493822).
doi: 10.1109/JCSSE53117.2021.9493822.
A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part II-Assessing Detection Speed.
(2018)
A Systematic Methodology for Comparing Batch Process Monitoring Methods: Part II-Assessing Detection Speed.
Industrial & Engineering Chemistry Research
57
(15)
:5338-5350.
doi: 10.1021/acs.iecr.7b0411.
(Impact factor, Quartile: 3.141, Q1).
Using Support Vector Regression and Hyperspectral Imaging for the Prediction of Oenological Parameters on Different Vintages and Varieties of Wine Grape Berries.
(2018)
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).
doi: 10.3390/rs10020312.
(Impact factor, Quartile: 3.406, Q2).
Characterization of neural network generalization in the determination of pH and anthocyanin content of wine grape in new vintages and varieties.
(2017)
Characterization of neural network generalization in the determination of pH and anthocyanin content of wine grape in new vintages and varieties.
Food Chemisry
218
:40-46.
ISSN: 0308-8146.
doi: 10.1016/j.foodchem.2016.09.024.
(Impact factor, Quartile: 4.529, Q1).
Comparison of different approaches for the prediction of sugar content in new vintages of whole Port wine grape berries using hyperspectral imaging.
(2017)
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
:244-254.
ISSN: 0168-1699.
doi: 10.1016/j.compag.2017.06.009.
(Impact factor, Quartile: 2.201, Q1).