36 citations · 92 across the 21 of their papers we have counts for
5 papers · 1 filter
SLURP: Side Learning Uncertainty for Regression Problems
Xuanlong Yu, Gianni Franchi, Emanuel Aldea
It has become critical for deep learning algorithms to quantify their output uncertainties to satisfy reliability constraints and provide accurate results. Uncertainty estimation f…
Robust Semantic Segmentation with Superpixel-Mix
Gianni Franchi, Nacim Belkhir, Mai Lan Ha +4
Along with predictive performance and runtime speed, reliability is a key requirement for real-world semantic segmentation. Reliability encompasses robustness, predictive uncertain…
Learning a Discriminant Latent Space with Neural Discriminant Analysis
Mai Lan Ha, Gianni Franchi, Emanuel Aldea +1
Discriminative features play an important role in image and object classification and also in other fields of research such as semi-supervised learning, fine-grained classification…
Learning Deep Morphological Networks with Neural Architecture Search
Yufei Hu, Nacim Belkhir, Jesus Angulo +2
Deep Neural Networks (DNNs) are generated by sequentially performing linear and non-linear processes. Using a combination of linear and non-linear procedures is critical for genera…
EXplainable Neural-Symbolic Learning (X-NeSyL) methodology to fuse deep learning representations with expert knowledge graphs: the MonuMAI cultural heritage use case
Natalia Díaz-Rodríguez, Alberto Lamas, Jules Sanchez +7
The latest Deep Learning (DL) models for detection and classification have achieved an unprecedented performance over classical machine learning algorithms. However, DL models are…