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Journal Articles
- 2023
[j16]Mee-Yung Shin
, Claudia Gonzalez Viejo, Eden Jane Tongson, Tonya Wiechel, Paul W. J. Taylor, Sigfredo Fuentes:
Early detection of Verticillium wilt of potatoes using near-infrared spectroscopy and machine learning modeling. Comput. Electron. Agric. 204: 107567 (2023)- 2022
- [j15]Marcos Carrasco-Benavides, Claudia Gonzalez Viejo, Eden Jane Tongson, Antonella Baffico-Hernández, Carlos Ávila-Sánchez, Marco Mora, Sigfredo Fuentes:
Water status estimation of cherry trees using infrared thermal imagery coupled with supervised machine learning modeling. Comput. Electron. Agric. 200: 107256 (2022) - [j14]Hai Ho Dac, Claudia Gonzalez Viejo, Nir Lipovetzky, Eden Jane Tongson, Frank R. Dunshea, Sigfredo Fuentes:
Livestock Identification Using Deep Learning for Traceability. Sensors 22(21): 8256 (2022) - [j13]Hanyue Feng, Claudia Gonzalez Viejo, Niloofar Vaghefi, Paul W. J. Taylor, Eden Jane Tongson, Sigfredo Fuentes:
Early Detection of Fusarium oxysporum Infection in Processing Tomatoes (Solanum lycopersicum) and Pathogen-Soil Interactions Using a Low-Cost Portable Electronic Nose and Machine Learning Modeling. Sensors 22(22): 8645 (2022) - 2021
- [j12]Sigfredo Fuentes, Eden Jane Tongson, Claudia Gonzalez Viejo:
Urban Green Infrastructure Monitoring Using Remote Sensing from Integrated Visible and Thermal Infrared Cameras Mounted on a Moving Vehicle. Sensors 21(1): 295 (2021) - [j11]Claudia Gonzalez Viejo, Eden Jane Tongson, Sigfredo Fuentes:
Integrating a Low-Cost Electronic Nose and Machine Learning Modelling to Assess Coffee Aroma Profile and Intensity. Sensors 21(6): 2016 (2021) - [j10]Sigfredo Fuentes, Eden Jane Tongson, Ranjith R. Unnithan, Claudia Gonzalez Viejo:
Early Detection of Aphid Infestation and Insect-Plant Interaction Assessment in Wheat Using a Low-Cost Electronic Nose (E-Nose), Near-Infrared Spectroscopy and Machine Learning Modeling. Sensors 21(17): 5948 (2021) - [j9]Sigfredo Fuentes, Eden Jane Tongson:
Editorial: Special Issue "Implementation of Sensors and Artificial Intelligence for Environmental Hazards Assessment in Urban, Agriculture and Forestry Systems". Sensors 21(19): 6383 (2021) - [j8]Sigfredo Fuentes, Claudia Gonzalez Viejo, Eden Jane Tongson, Nir Lipovetzky, Frank R. Dunshea:
Biometric Physiological Responses from Dairy Cows Measured by Visible Remote Sensing Are Good Predictors of Milk Productivity and Quality through Artificial Intelligence. Sensors 21(20): 6844 (2021) - [j7]Sigfredo Fuentes, Claudia Gonzalez Viejo, Chelsea Hall, Yidan Tang, Eden Jane Tongson:
Berry Cell Vitality Assessment and the Effect on Wine Sensory Traits Based on Chemical Fingerprinting, Canopy Architecture and Machine Learning Modelling. Sensors 21(21): 7312 (2021) - 2020
- [j6]Sigfredo Fuentes, Claudia Gonzalez Viejo, Brendan Cullen, Eden Jane Tongson, Surinder S. Chauhan, Frank R. Dunshea:
Artificial Intelligence Applied to a Robotic Dairy Farm to Model Milk Productivity and Quality based on Cow Data and Daily Environmental Parameters. Sensors 20(10): 2975 (2020) - [j5]Sigfredo Fuentes, Damir D. Torrico, Eden Jane Tongson, Claudia Gonzalez Viejo:
Machine Learning Modeling of Wine Sensory Profiles and Color of Vertical Vintages of Pinot Noir Based on Chemical Fingerprinting, Weather and Management Data. Sensors 20(13): 3618 (2020) - [j4]Sigfredo Fuentes, Vasiliki Summerson, Claudia Gonzalez Viejo, Eden Jane Tongson, Nir Lipovetzky, Kerry Wilkinson, Colleen Szeto, Ranjith R. Unnithan:
Assessment of Smoke Contamination in Grapevine Berries and Taint in Wines Due to Bushfires Using a Low-Cost E-Nose and an Artificial Intelligence Approach. Sensors 20(18): 5108 (2020) - [j3]Sigfredo Fuentes, Claudia Gonzalez Viejo, Surinder S. Chauhan, Aleena Joy, Eden Jane Tongson, Frank R. Dunshea:
Non-Invasive Sheep Biometrics Obtained by Computer Vision Algorithms and Machine Learning Modeling Using Integrated Visible/Infrared Thermal Cameras. Sensors 20(21): 6334 (2020) - 2019
- [j2]Sigfredo Fuentes, Eden Jane Tongson, Roberta De Bei, Claudia Gonzalez Viejo, Renata Ristic, Steve Tyerman, Kerry Wilkinson:
Non-Invasive Tools to Detect Smoke Contamination in Grapevine Canopies, Berries and Wine: A Remote Sensing and Machine Learning Modeling Approach. Sensors 19(15): 3335 (2019) - 2018
- [j1]Sigfredo Fuentes, Esther Hernández-Montes, J. M. Escalona, Josefina Bota, Claudia Gonzalez Viejo, Carlos Poblete-Echeverría, Eden Jane Tongson, H. Medrano:
Automated grapevine cultivar classification based on machine learning using leaf morpho-colorimetry, fractal dimension and near-infrared spectroscopy parameters. Comput. Electron. Agric. 151: 311-318 (2018)
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