JOSÉ SANTIAGO
TORRECILLA VELASCO
Catedrático de universidad
Publicaciones (174) Publicaciones de JOSÉ SANTIAGO TORRECILLA VELASCO
2023
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Application of residual neural networks to detect and quantify milk adulterations
Journal of Food Composition and Analysis, Vol. 122
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Deep quantification of a refined adulterant blended into pure avocado oil
Food Chemistry, Vol. 404
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Residual neural networks to quantify traces of melamine in yogurts through image deconvolution
Journal of Food Composition and Analysis, Vol. 118
2022
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Convolutional capture of the expansion of extra virgin olive oil droplets to quantify adulteration
Food Chemistry, Vol. 368
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Distinct thermal patterns to detect and quantify trace levels of wheat flour mixed into ground chickpeas
Food Chemistry, Vol. 384
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Is my food safe? – AI-based classification of lentil flour samples with trace levels of gluten or nuts
Food Chemistry, Vol. 386
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Single-digit ppm quantification of melamine in powdered milk driven by computer vision
Food Control, Vol. 131
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Standard photographs convolutionally processed to indirectly detect gluten in chickpea flour
Journal of Food Composition and Analysis, Vol. 110
2021
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Deep transfer learning to verify quality and safety of ground coffee
Food Control, Vol. 122
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Learning by playing via survey platforms to comprehend environmental management
Journal of Higher Education Theory and Practice, Vol. 21, Núm. 8, pp. 237-243
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Low requirement imaging enables sensitive and robust rice adulteration quantification via transfer learning
Food Control, Vol. 127
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Profiles of Volatile Biomarkers Detect Tuberculosis from Skin
Advanced Science, Vol. 8, Núm. 15
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Service-learning - Diagnostic technologies presented by Ph.D. students to help socially neglected people during the SARS-CoV-2 pandemic
International Conference on Higher Education Advances
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Thermal imaging of rice grains and flours to design convolutional systems to ensure quality and safety
Food Control, Vol. 121
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Thinking-Based Learning at Higher Education Levels: Implementation and Outcomes within a Chemical Engineering Class
Journal of Chemical Education, Vol. 98, Núm. 3, pp. 774-781
2020
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Cognitive chaos on spectrofluorometric data to quantitatively unmask adulterations of a PDO vinegar
Food Control, Vol. 108
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Convolutional decoding of thermographic images to locate and quantify honey adulterations
Talanta, Vol. 209
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Deep thermal imaging to compute the adulteration state of extra virgin olive oil
Computers and Electronics in Agriculture, Vol. 171
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Detection of adulterations of extra-virgin olive oil by means of infrared thermography
Olives and Olive Oil in Health and Disease Prevention (Elsevier), pp. 79-84
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Editorial: Artificial Intelligence in Chemistry
Frontiers in Chemistry