Zobrazeno 1 - 10
of 6 914
pro vyhledávání: '"A Bertoldo"'
Autor:
Riffel, Rogerio, Dahmer-Hahn, Luis G., Vazdekis, Alexandre, Davies, Richard, Rosario, David, Almeida, Cristina Ramos, Audibert, Anelise, Martin-Navarro, Ignacio, Martins, Lucimara Pires, Rodriguez-Ardila, Alberto, Riffel, Rogemar A., Storchi-Bergmann, Thaisa, Bertoldo-Coelho, Michele, Trevisan, Marina, Hicks, Erin, Muller, Allan Schnorr, Marinho, Lais Nery, Veilleux, Sylvain
Near-infrared long-slit spectroscopy has been used to study the stellar population (SP) of the low luminosity active galactic nuclei (AGN) and matched analogues (LLAMA) sample. To perform the SP fits we have employed the X-shooter simple stellar popu
Externí odkaz:
http://arxiv.org/abs/2405.00634
Autor:
Bertoldo-Coêlho, Michele, Riffel, Rogério, Trevisan, Marina, Dametto, Natacha Zanon, Dahmer-Hahn, Luis, Coelho, Paula, Martins, Lucimara, Ruschel-Dutra, Daniel, Vazdekis, Alexandre, Rodríguez-Ardila, Alberto, Chies-Santos, Ana L., Riffel, Rogemar A., La Barbera, Francesco, Navarro, Ignacio Martín, Barroso, Jesus Falcon, Moura, Tatiana
Most of the observed galaxies cannot be resolved into individual stars and are studied through their integrated spectrum using simple stellar populations (SSPs) models, with stellar libraries being a key ingredient in building them. Spectroscopic obs
Externí odkaz:
http://arxiv.org/abs/2404.14530
Recent advances in visual anomaly detection research have seen AUROC and AUPRO scores on public benchmark datasets such as MVTec and VisA converge towards perfect recall, giving the impression that these benchmarks are near-solved. However, high AURO
Externí odkaz:
http://arxiv.org/abs/2401.01984
Autor:
López-Núñez, David, Montserrat, Queralt Portell, Rius, Gemma, Bertoldo, Elia, Torras-Coloma, Alba, Martínez, M., Forn-Díaz, P.
We present a study of the superconducting penetration depth $\lambda$ in aluminum thin films of varying thickness. The range of thicknesses chosen spans from the thin-film regime to the regime approaching bulk behavior. The penetration depths observe
Externí odkaz:
http://arxiv.org/abs/2311.14119
Publikováno v:
22nd Brazilian Symposium on Computer Games and Digital Entertainment (SBGames 2023)
Creating and evaluating games manually is an arduous and laborious task. Procedural content generation can aid by creating game artifacts, but usually not an entire game. Evolutionary game design, which combines evolutionary algorithms with automated
Externí odkaz:
http://arxiv.org/abs/2310.20008
Autor:
Casti, Umberto, Baggio, Giacomo, Benozzo, Danilo, Zampieri, Sandro, Bertoldo, Alessandra, Chiuso, Alessandro
In this paper, we consider stable stochastic linear systems modeling whole-brain resting-state dynamics. We parametrize the state matrix of the system (effective connectivity) in terms of its steady-state covariance matrix (functional connectivity) a
Externí odkaz:
http://arxiv.org/abs/2310.07262
Autor:
Torras-Coloma, Alba, de Olcoz, Leyre Martínez, Céspedes, Eva, Bertoldo, Elia, López-Núñez, David, Paul, Sagar, Wernsdorfer, Wolfgang, Rius, Gemma, Forn-Díaz, Pol
We report the direct observation of superconductivity in nitridized-aluminum thin films. The films are produced by sputtering deposition of aluminum in a controlled mixture of nitrogen diluted in argon. The concentration of applied nitrogen directly
Externí odkaz:
http://arxiv.org/abs/2308.06240
Autor:
Gula, Tetiana, Bertoldo, João P C
Publikováno v:
Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, 2023, pp. 4110-4118
Anomaly detection (AD) in images, identifying significant deviations from normality, is a critical issue in computer vision. This paper introduces a novel approach to dimensionality reduction for AD using pre-trained convolutional neural network (CNN
Externí odkaz:
http://arxiv.org/abs/2308.04944
Publikováno v:
2023 Twelfth International Conference on Image Processing Theory, Tools and Applications (IPTA), Paris, France, 2023
Anomaly detection (AD) in images is a fundamental computer vision problem by deep learning neural network to identify images deviating significantly from normality. The deep features extracted from pretrained models have been proved to be essential f
Externí odkaz:
http://arxiv.org/abs/2307.11197
Autor:
Bertoldo, Joao P C, Arrustico, David
Publikováno v:
2023 Twelfth International Conference on Image Processing Theory, Tools and Applications (IPTA), Paris, France, 2023, pp. 1-6
This paper introduces a simplified variation of the PaDiM (Pixel-Wise Anomaly Detection through Instance Modeling) method for anomaly detection in images, fitting a single multivariate Gaussian (MVG) distribution to the feature vectors extracted from
Externí odkaz:
http://arxiv.org/abs/2307.06052