activity
20102023
most citedAutomatic Diagnosis of Schizophrenia in EEG Signals Using CNN-LSTM Models

205 citations · 525 across the 28 of their papers we have counts for

collaborators

30 papers

cs.LG2023

Semi-Supervised Machine Learning: a Homological Approach

Adrián Inés, César Domínguez, Jónathan Heras +2

In this paper we describe the mathematical foundations of a new approach to semi-supervised Machine Learning. Using techniques of Symbolic Computation and Computer Algebra, we appl…

cs.CV2022★ 11 cited

Automatic Diagnosis of Myocarditis Disease in Cardiac MRI Modality using Deep Transformers and Explainable Artificial Intelligence

Mahboobeh Jafari, Afshin Shoeibi, Navid Ghassemi +9

Myocarditis is a significant cardiovascular disease (CVD) that poses a threat to the health of many individuals by causing damage to the myocardium. The occurrence of microbes and…

cs.CV2022

Semi-Supervised Learning for Image Classification using Compact Networks in the BioMedical Context

Adrián Inés, Andrés Díaz-Pinto, César Domínguez +3

The development of mobile and on the edge applications that embed deep convolutional neural models has the potential to revolutionise biomedicine. However, most deep learning model…

cs.CV2022

A Topological Approach for Semi-Supervised Learning

Adrián Inés, César Domínguez, Jónathan Heras +2

Nowadays, Machine Learning and Deep Learning methods have become the state-of-the-art approach to solve data classification tasks. In order to use those methods, it is necessary to…

cs.CL2021

Text Classification Models for Form Entity Linking

María Villota, César Domínguez, Jónathan Heras +2

Forms are a widespread type of template-based document used in a great variety of fields including, among others, administration, medicine, finance, or insurance. The automatic ext…

cs.CV2021

Neural Style Transfer and Unpaired Image-to-Image Translation to deal with the Domain Shift Problem on Spheroid Segmentation

Manuel García-Domínguez, César Domínguez, Jónathan Heras +2

Background and objectives. Domain shift is a generalisation problem of machine learning models that occurs when the data distribution of the training set is different to the data d…