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pro vyhledávání: '"Camara, Pablo"'
Autor:
Hernández-Cámara, Pablo, Vila-Tomás, Jorge, Dauden-Oliver, Paula, Alabau-Bosque, Nuria, Laparra, Valero, Malo, Jesús
Autonomous driving is a challenging scenario for image segmentation due to the presence of uncontrolled environmental conditions and the eventually catastrophic consequences of failures. Previous work suggested that a biologically motivated computati
Externí odkaz:
http://arxiv.org/abs/2407.17829
We show that classical hue cancellation experiments lead to human-like opponent curves even if the task is done by trivial (identity) artificial networks. Specifically, human-like opponent spectral sensitivities always emerge in artificial networks a
Externí odkaz:
http://arxiv.org/abs/2303.08496
Subjective image quality measures based on deep neural networks are very related to models of visual neuroscience. This connection benefits engineering but, more interestingly, the freedom to optimize deep networks in different ways, make them an exc
Externí odkaz:
http://arxiv.org/abs/2302.13345
One of the key problems in computer vision is adaptation: models are too rigid to follow the variability of the inputs. The canonical computation that explains adaptation in sensory neuroscience is divisive normalization, and it has appealing effects
Externí odkaz:
http://arxiv.org/abs/2203.13558
Akademický článek
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Publikováno v:
In Pattern Recognition Letters September 2023 173:64-71
The scale and complexity of modern data sets and the limitations associated with testing large numbers of hypotheses underline the need for feature selection methods. Spectral techniques rank features according to their degree of consistency with an
Externí odkaz:
http://arxiv.org/abs/1811.03377
The recent explosion of genomic data has underscored the need for interpretable and comprehensive analyses that can capture complex phylogenetic relationships within and across species. Recombination, reassortment and horizontal gene transfer constit
Externí odkaz:
http://arxiv.org/abs/1505.05815
Persistent homology computes topological invariants from point cloud data. Recent work has focused on developing statistical methods for data analysis in this framework. We show that, in certain models, parametric inference can be performed using sta
Externí odkaz:
http://arxiv.org/abs/1406.4582
Closed string fluxes induce generically SUSY-breaking soft terms on supersymmetric type IIB orientifold compactifications with D3/D7 branes. This was studied in the past by inserting those fluxes on the DBI+CS actions for adjoint D3/D7 fields, where
Externí odkaz:
http://arxiv.org/abs/1404.0817