Search Results for author:
Found 12 papers, 3 papers with code
FlightScope: A Deep Comprehensive Assessment of Aircraft Detection Algorithms in Satellite Imagery
Object detection in remotely sensed satellite pictures is fundamental in many fields such as biophysical, and environmental monitoring.
FusionVision: A comprehensive approach of 3D object reconstruction and segmentation from RGB-D cameras using YOLO and fast segment anything
Therefore, this paper introduces FusionVision, an exhaustive pipeline adapted for the robust 3D segmentation of objects in RGB-D imagery.
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).
On the High Symmetry of Neural Network Functions
This work shows how the neural network function has a number of equivalent minima, in other words minima that give the same value for the loss function and the same exact output, that grows factorially with the number of neurons in each layer for feed forward neural network or with the number of filters in a convolutional neural networks.
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.
Optical oxygen sensing with artificial intelligence
In the classical approach, this change is related to an oxygen concentration using the Stern-Volmer equation.
