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Found 9 papers, 1 papers with code
Symbrain: A large-scale dataset of MRI images for neonatal brain symmetry analysis
Furthermore, this dataset can contribute to the research and development of methods using the relative symmetry of the two brain hemispheres for crucial diagnosis and treatment planning.
Shedding Light on the Ageing of Extra Virgin Olive Oil: Probing the Impact of Temperature with Fluorescence Spectroscopy and Machine Learning Techniques
This work systematically investigates the oxidation of extra virgin olive oil (EVOO) under accelerated storage conditions with UV absorption and total fluorescence spectroscopy.
Dataset of Fluorescence Spectra and Chemical Parameters of Olive Oils
The dataset includes the values of the following chemical parameters for each olive oil sample: acidity, peroxide value, K270, K232, ethyl esters, and the quality of the samples (EVOO, VOO, or LOO).
New Metric Formulas that Include Measurement Errors in Machine Learning for Natural Sciences
This paper addresses this deficiency by deriving formulas for commonly used metrics (both for regression and classification problems) that take into account measurement errors of target variables.
Physico-chemical properties extraction from the fluorescence spectrum with 1D-convolutional neural networks: application to olive oil
One of the main challenges for olive oil producers is the ability to asses and control the quality during the production cycle.
A Model-Agnostic Algorithm for Bayes Error Determination in Binary Classification
This paper presents the intrinsic limit determination algorithm (ILD Algorithm), a novel technique to determine the best possible performance, measured in terms of the AUC (area under the ROC curve) and accuracy, that can be obtained from a specific dataset in a binary classification problem with categorical features {\sl regardless} of the model used.
Exploration of Spanish Olive Oil Quality with a Miniaturized Low-Cost Fluorescence Sensor and Machine Learning Techniques
Extra virgin olive oil (EVOO) is the highest quality of olive oil and is characterized by highly beneficial nutritional properties.
Multi-Task Learning for Multi-Dimensional Regression: Application to Luminescence Sensing
The classical approach to non-linear regression in physics, is to take a mathematical model describing the functional dependence of the dependent variable from a set of independent variables, and then, using non-linear fitting algorithms, extract the parameters used in the modeling.
Optical oxygen sensing with artificial intelligence
In the classical approach, this change is related to an oxygen concentration using the Stern-Volmer equation.
