4 papers
PD-Loss: Proxy-Decidability for Efficient Metric Learning
Pedro Silva, Guilherme A. L. Silva, Pablo Coelho +4
Deep Metric Learning (DML) aims to learn embedding functions that map semantically similar inputs to proximate points in a metric space while separating dissimilar ones. Existing m…
Deep Learning for School Dropout Detection: A Comparison of Tabular and Graph-Based Models for Predicting At-Risk Students
Pablo G. Almeida, Guilherme A. L. Silva, Valéria Santos +3
Student dropout is a significant challenge in educational systems worldwide, leading to substantial social and economic costs. Predicting students at risk of dropout allows for tim…
Investigating the Impact of Large-Scale Pre-training on Nutritional Content Estimation from 2D Images
Michele Andrade, Guilherme A. L. Silva, Valéria Santos +2
Estimating the nutritional content of food from images is a critical task with significant implications for health and dietary monitoring. This is challenging, especially when rely…
A Systematic Review of ECG Arrhythmia Classification: Adherence to Standards, Fair Evaluation, and Embedded Feasibility
Guilherme Silva, Pedro Silva, Gladston Moreira +3
The classification of electrocardiogram (ECG) signals is crucial for early detection of arrhythmias and other cardiac conditions. However, despite advances in machine learning, man…