Zobrazeno 1 - 10
of 8 092
pro vyhledávání: '"A P, Steinmetz"'
Autor:
Ratcliffe, Bridget, Khoperskov, Sergey, Minchev, Ivan, Lee, Nathan D., Buck, Tobias, Marques, Léa, Lu, Lucy, Steinmetz, Matthias
Recent works identified a way to recover the time evolution of a galaxy's disk metallicity gradient from the shape of its age--metallicity relation. However, the success of the method is dependent on how the width of the star-forming region evolves o
Externí odkaz:
http://arxiv.org/abs/2410.17326
Human-in-the-loop Reasoning For Traffic Sign Detection: Collaborative Approach Yolo With Video-llava
Autor:
Azarafza, Mehdi, Idrees, Fatima, Bejnordi, Ali Ehteshami, Steinmetz, Charles, Henkler, Stefan, Rettberg, Achim
Traffic Sign Recognition (TSR) detection is a crucial component of autonomous vehicles. While You Only Look Once (YOLO) is a popular real-time object detection algorithm, factors like training data quality and adverse weather conditions (e.g., heavy
Externí odkaz:
http://arxiv.org/abs/2410.05096
Autor:
Rafelski, Johann, Birrell, Jeremiah, Grayson, Christopher, Steinmetz, Andrew, Yang, Cheng Tao
We describe in the context of the particle physics (PP) standard model (SM) `PP-SM' the understanding of the primordial properties and composition of the Universe in the temperature range $130\GeV>T>20\keV$. The Universe evolution is described using
Externí odkaz:
http://arxiv.org/abs/2409.19031
Scholarly communication is a rapid growing field containing a wealth of knowledge. However, due to its unstructured and document format, it is challenging to extract useful information from them through conventional document retrieval methods. Schola
Externí odkaz:
http://arxiv.org/abs/2409.09010
Autor:
Lübeck, Konstantin, Jung, Alexander Louis-Ferdinand, Wedlich, Felix, Müller, Mika Markus, Peccia, Federico Nicolás, Thömmes, Felix, Steinmetz, Jannik, Biermaier, Valentin, Frischknecht, Adrian, Bernardo, Paul Palomero, Bringmann, Oliver
Implementing Deep Neural Networks (DNNs) on resource-constrained edge devices is a challenging task that requires tailored hardware accelerator architectures and a clear understanding of their performance characteristics when executing the intended A
Externí odkaz:
http://arxiv.org/abs/2409.08595
Autor:
Kich, Victor Augusto, Bottega, Jair Augusto, Steinmetz, Raul, Grando, Ricardo Bedin, Yorozu, Ayano, Ohya, Akihisa
In this work, we present Curled-Dreamer, a novel reinforcement learning algorithm that integrates contrastive learning into the DreamerV3 framework to enhance performance in visual reinforcement learning tasks. By incorporating the contrastive loss f
Externí odkaz:
http://arxiv.org/abs/2408.05781
Autor:
Kich, Victor Augusto, Bottega, Jair Augusto, Steinmetz, Raul, Grando, Ricardo Bedin, Yorozu, Ayano, Ohya, Akihisa
Kolmogorov-Arnold Networks (KANs) have shown potential as an alternative to Multi-Layer Perceptrons (MLPs) in neural networks, providing universal function approximation with fewer parameters and reduced memory usage. In this paper, we explore the us
Externí odkaz:
http://arxiv.org/abs/2408.04841
Autor:
Vanka, Soumya Sai, Steinmetz, Christian, Rolland, Jean-Baptiste, Reiss, Joshua, Fazekas, George
Mixing style transfer automates the generation of a multitrack mix for a given set of tracks by inferring production attributes from a reference song. However, existing systems for mixing style transfer are limited in that they often operate only on
Externí odkaz:
http://arxiv.org/abs/2407.08889
Autor:
Khalatyan, A., Anders, F., Chiappini, C., Queiroz, A. B. A., Nepal, S., Ponte, M. dal, Jordi, C., Guiglion, G., Valentini, M., Elipe, G. Torralba, Steinmetz, M., Pantaleoni-González, M., Malhotra, S., Jiménez-Arranz, Ó., Enke, H., Casamiquela, L., Ardèvol, J.
Publikováno v:
A&A 691, A98 (2024)
In this paper, we explore the feasibility of using machine learning regression as a method of extracting basic stellar parameters and line-of-sight extinctions from spectro-photometric data. We built a stable gradient-boosted random-forest regressor
Externí odkaz:
http://arxiv.org/abs/2407.06963
Autor:
Richard, Johan, Giroud, Rémi, Laurent, Florence, Krajnović, Davor, Jeanneau, Alexandre, Bacon, Roland, Abreu, Manuel, Adamo, Angela, Araujo, Ricardo, Bouché, Nicolas, Brinchmann, Jarle, Cai, Zhemin, Castro, Norberto, Calcines, Ariadna, Chapuis, Diane, Claeyssens, Adélaïde, Cortese, Luca, Daddi, Emanuele, Davison, Christopher, Goodwin, Michael, Harris, Robert, Hayes, Matthew, Jauzac, Mathilde, Kelz, Andreas, Kneib, Jean-Paul, Lanotte, Audrey A., Lawrence, Jon, Bouteiller, Vianney Le, Breton, Rémy Le, Lehnert, Matthew, Sanchez, Angel Lopez, McGregor, Helen, McLeod, Anna F., Monteiro, Manuel, Morris, Simon, Opitom, Cyrielle, Pécontal, Arlette, Robertson, David, Roth, Martin M., van de Sande, Jesse, Smith, Russell, Steinmetz, Matthias, Swinbank, Mark, Urrutia, Tanya, Verhamme, Anne, Weilbacher, Peter M., Wendt, Martin, Wildi, François, Zheng, Jessica, consortium, The BlueMUSE
BlueMUSE is a blue-optimised, medium spectral resolution, panoramic integral field spectrograph under development for the Very Large Telescope (VLT). With an optimised transmission down to 350 nm, spectral resolution of R$\sim$3500 on average across
Externí odkaz:
http://arxiv.org/abs/2406.13914