24 citations · 77 across the 14 of their papers we have counts for
17 papers
Self-Supervised Pre-Training Boosts Semantic Scene Segmentation on LiDAR Data
Mariona Carós, Ariadna Just, Santi Seguí +1
Airborne LiDAR systems have the capability to capture the Earth's surface by generating extensive point cloud data comprised of points mainly defined by 3D coordinates. However, la…
Object Segmentation of Cluttered Airborne LiDAR Point Clouds
Mariona Caros, Ariadna Just, Santi Segui +1
Airborne topographic LiDAR is an active remote sensing technology that emits near-infrared light to map objects on the Earth's surface. Derived products of LiDAR are suitable to se…
Time-based Self-supervised Learning for Wireless Capsule Endoscopy
Guillem Pascual, Pablo Laiz, Albert García +3
State-of-the-art machine learning models, and especially deep learning ones, are significantly data-hungry; they require vast amounts of manually labeled samples to function correc…
Deep Non-Crossing Quantiles through the Partial Derivative
Axel Brando, Joan Gimeno, Jose A. Rodríguez-Serrano +1
Quantile Regression (QR) provides a way to approximate a single conditional quantile. To have a more informative description of the conditional distribution, QR can be merged with…
Algorithmic Causal Effect Identification with causaleffect
Martí Pedemonte, Jordi Vitrià, Álvaro Parafita
Our evolution as a species made a huge step forward when we understood the relationships between causes and effects. These associations may be trivial for some events, but they are…
Graph Convolutional Embeddings for Recommender Systems
Paula Gómez Duran, Alexandros Karatzoglou, Jordi Vitrià +2
Modern recommender systems (RS) work by processing a number of signals that can be inferred from large sets of user-item interaction data. The main signal to analyze stems from the…