Zobrazeno 1 - 10
of 13 427
pro vyhledávání: '"Couso A"'
Autor:
Crespo Navarro, Elena
Publikováno v:
Revista Española de Derecho Internacional, 2022 Jan 01. 74(1), 241-252.
Externí odkaz:
https://www.jstor.org/stable/27116576
Autor:
Crespo Navarro, Elena
Publikováno v:
Revista Española de Derecho Internacional, 2020 Jul 01. 72(2), 197-234.
Externí odkaz:
https://www.jstor.org/stable/26927916
Autor:
María Rocío Ramos Ramos
Publikováno v:
Erebea, Vol 12, Iss 2 (2023)
Externí odkaz:
https://doaj.org/article/1a9d58cb3134453999a12bc917ea2e23
Autor:
Montalvo, Javier, Alcover-Couso, Roberto, Carballeira, Pablo, García-Martín, Álvaro, SanMiguel, Juan C., Escudero-Viñolo, Marcos
This paper introduces a novel synthetic dataset that captures urban scenes under a variety of weather conditions, providing pixel-perfect, ground-truth-aligned images to facilitate effective feature alignment across domains. Additionally, we propose
Externí odkaz:
http://arxiv.org/abs/2412.16592
Segmentation models are typically constrained by the categories defined during training. To address this, researchers have explored two independent approaches: adapting Vision-Language Models (VLMs) and leveraging synthetic data. However, VLMs often
Externí odkaz:
http://arxiv.org/abs/2412.09240
Merging parameters of multiple models has resurfaced as an effective strategy to enhance task performance and robustness, but prior work is limited by the high costs of ensemble creation and inference. In this paper, we leverage the abundance of free
Externí odkaz:
http://arxiv.org/abs/2409.15813
Autor:
Couso-Queiruga, Emilio, Avila-Ortiz, Gustavo, Porto Barboza, Eliane, Chambrone, Leandro, Gencay Keceli, Huseyn, Tolga Yilmaz, Birtain, Moreira Rodrigues, Diogo
Publikováno v:
International Journal of Periodontics & Restorative Dentistry; Nov/Dec2024, Vol. 44 Issue 6, p629-638b, 12p
Autor:
Fernández Liesa, Carlos R.
Publikováno v:
Revista Española de Derecho Internacional, 2011 Jul 01. 63(2), 145-160.
Externí odkaz:
https://www.jstor.org/stable/26177260
In unsupervised domain adaptation (UDA), where models are trained on source data (e.g., synthetic) and adapted to target data (e.g., real-world) without target annotations, addressing the challenge of significant class imbalance remains an open issue
Externí odkaz:
http://arxiv.org/abs/2407.01327
Autor:
Núria Garcia
Publikováno v:
Ciències, Vol 1, Iss 40 (2020)
Over the last few years, STEM education has been gaining momentum from both public institutions and the private sector. Much is said and speculated about the hidden interests that may be behind this impulse, dark interests, which aim to perpetuate th
Externí odkaz:
https://doaj.org/article/a04003682a344a16b8b9cf3ed06c129d