63 citations · 125 across the 6 of their papers we have counts for
6 papers
Spatially-Aware Evaluation Framework for Aerial LiDAR Point Cloud Semantic Segmentation: Distance-Based Metrics on Challenging Regions
Alex Salvatierra, José Antonio Sanz, Christian Gutiérrez +1
Semantic segmentation metrics for 3D point clouds, such as mean Intersection over Union (mIoU) and Overall Accuracy (OA), present two key limitations in the context of aerial LiDAR…
Benchmarking Deep Learning Models for Aerial LiDAR Point Cloud Semantic Segmentation under Real Acquisition Conditions: A Case Study in Navarre
Alex Salvatierra, José Antonio Sanz, Christian Gutiérrez +1
Recent advances in deep learning have significantly improved 3D semantic segmentation, but most models focus on indoor or terrestrial datasets. Their behavior under real aerial acq…
Towards interval uncertainty propagation control in bivariate aggregation processes and the introduction of width-limited interval-valued overlap functions
Tiago da Cruz Asmus, Graçaliz Pereira Dimuro, Benjamín Bedregal +3
Overlap functions are a class of aggregation functions that measure the overlapping degree between two values. Interval-valued overlap functions were defined as an extension to exp…
Motor-Imagery-Based Brain Computer Interface using Signal Derivation and Aggregation Functions
Javier Fumanal-Idocin, Yu-Kai Wang, Chin-Teng Lin +3
Brain Computer Interface technologies are popular methods of communication between the human brain and external devices. One of the most popular approaches to BCI is Motor Imagery.…
Interval-valued aggregation functions based on moderate deviations applied to Motor-Imagery-Based Brain Computer Interface
Javier Fumanal-Idocin, Zdenko Takáč, Javier Fernández Jose Antonio Sanz +4
In this work we study the use of moderate deviation functions to measure similarity and dissimilarity among a set of given interval-valued data. To do so, we introduce the notion o…
CFM-BD: a distributed rule induction algorithm for building Compact Fuzzy Models in Big Data classification problems
Mikel Elkano, Jose Sanz, Edurne Barrenechea +2
Interpretability has always been a major concern for fuzzy rule-based classifiers. The usage of human-readable models allows them to explain the reasoning behind their predictions…