Zobrazeno 1 - 10
of 22 540
pro vyhledávání: '"ZARATE, A."'
Autor:
Offidani, Mauro Nievas, Roffet, Facundo, Delrieux, Claudio Augusto, Galtier, Maria Carolina Gonzalez, Zarate, Marcos
Classification is a fundamental task in machine learning. While conventional methods-such as binary, multiclass, and multi-label classification-are effective for simpler problems, they may not adequately address the complexities of some real-world sc
Externí odkaz:
http://arxiv.org/abs/2412.14299
Autor:
Obrist, Jan, Zamora, Miguel, Zheng, Hehui, Hinchet, Ronan, Ozdemir, Firat, Zarate, Juan, Katzschmann, Robert K., Coros, Stelian
Data-driven methods have shown great potential in solving challenging manipulation tasks, however, their application in the domain of deformable objects has been constrained, in part, by the lack of data. To address this, we propose PokeFlex, a datas
Externí odkaz:
http://arxiv.org/abs/2410.07688
Autor:
Obrist, Jan, Zamora, Miguel, Zheng, Hehui, Zarate, Juan, Katzschmann, Robert K., Coros, Stelian
Advancing robotic manipulation of deformable objects can enable automation of repetitive tasks across multiple industries, from food processing to textiles and healthcare. Yet robots struggle with the high dimensionality of deformable objects and the
Externí odkaz:
http://arxiv.org/abs/2409.17124
Autor:
Sedar, Roshan, Kalalas, Charalampos, Dini, Paolo, Vazquez-Gallego, Francisco, Alonso-Zarate, Jesus, Alonso, Luis
Vehicular mobility underscores the need for collaborative misbehavior detection at the vehicular edge. However, locally trained misbehavior detection models are susceptible to adversarial attacks that aim to deliberately influence learning outcomes.
Externí odkaz:
http://arxiv.org/abs/2409.02844
Autor:
Hàn, Hiêp, Lang, Richard, Marciano, João Pedro, Pavez-Signé, Matías, Sanhueza-Matamala, Nicolás, Treglown, Andrew, Zárate-Guerén, Camila
We study conditions under which an edge-coloured hypergraph has a particular substructure that contains more than the trivially guaranteed number of monochromatic edges. Our main result solves this problem for perfect matchings under minimum degree c
Externí odkaz:
http://arxiv.org/abs/2408.11016
Autor:
Perez-Zarate, Ezequiel, Ramos-Soto, Oscar, Liu, Chunxiao, Oliva, Diego, Perez-Cisneros, Marco
Low-light image enhancement is an important task in computer vision, essential for improving the visibility and quality of images captured in non-optimal lighting conditions. Inadequate illumination can lead to significant information loss and poor i
Externí odkaz:
http://arxiv.org/abs/2407.19708
Autor:
Vallejo-Fabila, Isaias, Kumar-Das, Adway, Zarate-Herrada, David A., Matsoukas-Roubeas, Apollonas S., Torres-Herrera, E. Jonathan, Santos, Lea F.
We investigate how the dynamical fluctuations of many-body quantum systems out of equilibrium can be mitigated when they are opened to a dephasing environment. We consider the survival probability (spectral form factor with a filter) evolving under d
Externí odkaz:
http://arxiv.org/abs/2406.14647
Autor:
Nolasco-Altamirano, D., Romero-Nuñez, C. S., Alonso-Sotolongoza, A., Benavente, J. F., García-Salcedo, R., García-Garduño, O. A., Zarate-Medina, J., Correcher, V., Montalvo, T. Rivera
{We herein report on the calculation of thermoluminescence (TL) kinetic parameters determined from the TL emission of synthetic GdAlO3 (GAO) phosphors prepared by the co-precipitation method. The sample, characterized by means of X-ray diffraction wi
Externí odkaz:
http://arxiv.org/abs/2406.01312
Autor:
Wang, Wenbo, Ho, Hsuan-I, Guo, Chen, Rong, Boxiang, Grigorev, Artur, Song, Jie, Zarate, Juan Jose, Hilliges, Otmar
The studies of human clothing for digital avatars have predominantly relied on synthetic datasets. While easy to collect, synthetic data often fall short in realism and fail to capture authentic clothing dynamics. Addressing this gap, we introduce 4D
Externí odkaz:
http://arxiv.org/abs/2404.18630
Each decision-making tool should be tested and validated in real case studies to be practical and fit to global problems. The application of multi-criteria decision-making methods (MCDM) is currently a trend to rank alternatives. In the literature, t
Externí odkaz:
http://arxiv.org/abs/2405.02324