4 papers · 1 filter
An explainable three dimension framework to uncover learning patterns: A unified look in variable sulci recognition
Michail Mamalakis, Heloise de Vareilles, Atheer AI-Manea +8
The significant features identified in a representative subset of the dataset during the learning process of an artificial intelligence model are referred to as a 'global' explanat…
Statistical Agnostic Regression: a machine learning method to validate regression models
Juan M Gorriz, J. Ramirez, F. Segovia +3
Regression analysis is a central topic in statistical modeling, aimed at estimating the relationships between a dependent variable, commonly referred to as the response variable, a…
Is K-fold cross validation the best model selection method for Machine Learning?
Juan M Gorriz, R. Martin Clemente, F Segovia +3
As a technique that can compactly represent complex patterns, machine learning has significant potential for predictive inference. K-fold cross-validation (CV) is the most common a…
Contrastive-Adversarial and Diffusion: Exploring pre-training and fine-tuning strategies for sulcal identification
Michail Mamalakis, Héloïse de Vareilles, Shun-Chin Jim Wu +7
In the last decade, computer vision has witnessed the establishment of various training and learning approaches. Techniques like adversarial learning, contrastive learning, diffusi…