Zobrazeno 1 - 10
of 185
pro vyhledávání: '"Matias del Campo"'
Publikováno v:
Dimensions (10746536); 2022, Vol. 35, p80-91, 12p
Autor:
Andrónico Neira-Carrillo, Ignacio A. Zárate, Eddie Nieto, Nicole Butto-Miranda, Lorena Lobos-González, Matias Del Campo-Smith, Daniel A. Palacio, Bruno F. Urbano
Publikováno v:
Nanomaterials, Vol 12, Iss 21, p 3903 (2022)
Potential drug-eluting scaffolds of electrospun poly(acrylic acid-co-styrene sulfonate) P(AA-co-SS) in clonogenic assays using tumorigenic gastric and ovarian cancer cells were tested in vitro. Electrospun polymer nanofiber (EPnF) meshes of PAA and P
Externí odkaz:
https://doaj.org/article/7c49eeb4ffd4496495d77f211b1acd0f
Publikováno v:
Machine Learning and the City. :183-188
Autor:
Simon Sadler, Adnan Z. Morshed, Aneesha Dharwadker, Ozayr Saloojee, Thandi Loewenson, Anya Sirota, Adam Yarinsky, Matias del Campo, Germane Barnes, Irene Cheng
Publikováno v:
Places Journal.
Autor:
Andrónico, Neira-Carrillo, Ignacio A, Zárate, Eddie, Nieto, Nicole, Butto-Miranda, Lorena, Lobos-González, Matias, Del Campo-Smith, Daniel A, Palacio, Bruno F, Urbano
Publikováno v:
Nanomaterials (Basel, Switzerland). 12(21)
Potential drug-eluting scaffolds of electrospun poly(acrylic acid
Autor:
Matias del Campo
Publikováno v:
Architectural Intelligence. 1
The purpose of this article is to discuss the application of artificial intelligence (AI) in the design of the Deep House project (Fig. 1), an attempt to use estrangement as a method to emancipate a house from a canonical approach to the progressive
Autor:
Matias del Campo, Sandra Manninger
Publikováno v:
The Routledge Companion to Ecological Design Thinking ISBN: 9781003183181
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::52e2138e0af3aeb251fd28f310a54ac5
https://doi.org/10.4324/9781003183181-8
https://doi.org/10.4324/9781003183181-8
Publikováno v:
International Journal of Architectural Computing. :147807712311719
Publikováno v:
International Journal of Architectural Computing. 19:88-103
There are particular similarities in how machines learn about the nature of their environment, and how humans learn to process visual stimuli. Machine Learning (ML), more specifically Deep Neural network algorithms rely on expansive image databases a