Zobrazeno 1 - 10
of 1 261
pro vyhledávání: '"Jose Alvarado"'
Publikováno v:
PizzaMarketplace.com. 3/8/2023, pN.PAG-N.PAG. 1p.
Publikováno v:
Diálogos: Artes, Letras, Ciencias humanas, 1974 Nov 01. 106 (60), 39-40.
Externí odkaz:
https://www.jstor.org/stable/27933295
Autor:
Poot, Jacques
Publikováno v:
The International Migration Review, 1999 Oct 01. 33(3), 767-769.
Externí odkaz:
https://www.jstor.org/stable/2547535
Autor:
Prinz, Christopher
Publikováno v:
European Journal of Population / Revue Européenne de Démographie, 1999 Mar 01. 15(1), 99-100.
Externí odkaz:
https://www.jstor.org/stable/20164056
Autor:
Luis Gutierrez, Beth Polidoro, David Obura, Francoise Cabada-Blanco, Christi Linardich, Emma Pettersson, Paul Pearce-Kelly, Krista Kemppinen, Juan Jose Alvarado, Lorenzo Alvarez-Filip, Anastazia Banaszak, Pilar Casado de Amezua, James Crabbe, Aldo Croquer, Joshua Feingold, Elizabeth Goergen, Stefano Goffredo, Bert Hoeksema, Danwei Huang, Emma Kennedy, Diego Kersting, Marcelo Kitahara, Petar Kružić, Margaret Miller, Flavia Nunes, Juan Pablo Quimbayo, Andrea Rivera-Sosa, Rosa Rodríguez-Martínez, Nadia Santodomingo, Michael Sweet, Mark Vermeij, Estrella Villamizar, Greta Aeby, Khatija Alliji, Daniel Bayley, Elena Couce, Benjamin Cowburn, C Isabel Nuñez Lendo, Sean Porter, Kaveh Samimi-Namin, Tom Shlesinger, Bryan Wilson
Publikováno v:
PLoS ONE, Vol 19, Iss 11, p e0309354 (2024)
Atlantic reef-building corals and coral reefs continue to experience extensive decline due to increased stressors related to climate change, disease, pollution, and numerous anthropogenic threats. To understand the impact of ocean warming and reef lo
Externí odkaz:
https://doaj.org/article/6a63c1b7488743878ab7ac8649c8d971
Autor:
Penner, Rudolph G.
Publikováno v:
Journal of Economic Literature, 1999 Sep 01. 37(3), 1196-1197.
Externí odkaz:
https://www.jstor.org/stable/2564889
Autor:
Kumar, Shachi H, Okur, Eda, Sahay, Saurav, Leanos, Juan Jose Alvarado, Huang, Jonathan, Nachman, Lama
With the recent advancements in AI, Intelligent Virtual Assistants (IVA) have become a ubiquitous part of every home. Going forward, we are witnessing a confluence of vision, speech and dialog system technologies that are enabling the IVAs to learn a
Externí odkaz:
http://arxiv.org/abs/1812.08407
We propose an efficient end-to-end convolutional neural network architecture, AclNet, for audio classification. When trained with our data augmentation and regularization, we achieved state-of-the-art performance on the ESC-50 corpus with 85:65% accu
Externí odkaz:
http://arxiv.org/abs/1811.06669