Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Jorge L. Charco"'
Autor:
César Espin-Riofrio, Jorge L. Charco, Johanna Zumba Gamboa, Verónica Mendoza Morán, Arturo Montejo-Ráez
Publikováno v:
Proceedings of the 20th LACCEI International Multi-Conference for Engineering, Education and Technology: “Education, Research and Leadership in Post-pandemic Engineering: Resilient, Inclusive and Sustainable Actions”.
Publikováno v:
Intelligent Systems Reference Library ISBN: 9783031063060
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b03cda53499c153fd972e65f659324e9
https://doi.org/10.1007/978-3-031-06307-7_5
https://doi.org/10.1007/978-3-031-06307-7_5
Autor:
Telmo Roque-Colt, Jorge L. Charco, Angélica Cruz-Chóez, Kevin Egas-Arizala, Charles M. Pérez-Espinoza
Publikováno v:
Systems and Information Sciences ISBN: 9783030591939
This paper presents a Long-Short Term Memory, as a special kind of Recurrent Neural Network, capable of learning long-term dependencies to estimate the temperature. In order to improve the performance of the proposed model, a multivariate time series
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::afd10e9e2692843506fa926bfea6ddd2
https://doi.org/10.1007/978-3-030-59194-6_4
https://doi.org/10.1007/978-3-030-59194-6_4
Publikováno v:
VISIGRAPP (4: VISAPP)
Publikováno v:
Image and Vision Computing. 110:104182
This paper presents a domain adaptation strategy to efficiently train network architectures for estimating the relative camera pose in multi-view scenarios. The network architectures are fed by a pair of simultaneously acquired images, hence in order
Publikováno v:
RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname
instname
[EN] Healthy eating habits involve controlling your diet. It is important to know how to interpret the nutritional information of the packaged foods that you consume. These packaged foods are usually processed and contain carbohydrates and fats. Moni
Publikováno v:
SITIS
This paper proposes to use a deep learning network architecture for relative camera pose estimation on a multi-view environment. The proposed network is a variant architecture of AlexNet to use as regressor for prediction the relative translation and