Zobrazeno 1 - 10
of 14
pro vyhledávání: '"Leonardo Ravaglia"'
Autor:
Ferreira Gonçalves, Leonardo Ravaglia1 leonardorfg@gmail.com, Geralda de Almeida, Maria1 mgdealmeida10@gmail.com
Publikováno v:
Boletim de Geografia. mai-ago2020, Vol. 38 Issue 2, p18-32. 15p.
Publikováno v:
Boletim de Geografia. 38:18-32
Objetiva-se com este artigo fomentar a reflexão sobre o conceito de identidade territorial de forma relacional a outros conceitos comuns à Geografia e à Sociologia, como território, territorialidade, ideologia e Estado. Para isso, realiza-se pesq
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07f5d436f0f3e65e3cb0c28b834acf11
https://doi.org/10.4025/bolgeogr.v38i2.40032
https://doi.org/10.4025/bolgeogr.v38i2.40032
Publikováno v:
Hospitalidade ISBN: 9786554470179
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ffdd986b343d2d7d490b92901be429a
https://doi.org/10.29327/5131554.1-4
https://doi.org/10.29327/5131554.1-4
Autor:
Davide Nadalini, Manuele Rusci, Giuseppe Tagliavini, Leonardo Ravaglia, Luca Benini, Francesco Conti
Publikováno v:
Lecture Notes in Computer Science ISBN: 9783031150739
An open challenge in making Internet-of-Things sensor nodes "smart'' and self-adaptive is to enable on-chip Deep Neural Network (DNN) training on Ultra-Low-Power (ULP) microcontroller units (MCUs). To this aim, we present a framework, based on PULP-T
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5c4e934716d5dcc64dbd615e6a8417a2
https://hdl.handle.net/11585/900686
https://hdl.handle.net/11585/900686
Autor:
Leonardo Ravaglia, Francesco Conti, Manuele Rusci, Alessandro Capotondi, Davide Nadalini, Luca Benini
In the last few years, research and development on Deep Learning models and techniques for ultra-low-power devices in a word, TinyML has mainly focused on a train-then-deploy assumption, with static models that cannot be adapted to newly collected da
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1f551185826fd11c021615df0ee10d8e
Autor:
Luca Benini, Cristian Sarti, Simone Benatt, Marcello Zanghieri, Leonardo Ravaglia, Alessio Burrello
Publikováno v:
2021 IEEE Sensors Applications Symposium (SAS)
Human-machine interaction is showing promising results for robotic prosthesis control and rehabilitation. In these fields, hand movement recognition via surface electromyographic (sEMG) signals is one of the most promising approaches. However, it sti
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::716151d619d32913acd57112abd8e893
https://hdl.handle.net/11380/1264859
https://hdl.handle.net/11380/1264859
Autor:
Vincenzo Lomonaco, Alessandro Capotondi, Lorenzo Pellegrini, Manuele Rusci, Davide Maltoni, Luca Benini, Leonardo Ravaglia, Francesco Conti
Publikováno v:
SiPS
AI-powered edge devices currently lack the ability to adapt their embedded inference models to the ever-changing environment. To tackle this issue, Continual Learning (CL) strategies aim at incrementally improving the decision capabilities based on n
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8fca09f8839abb2f8f226191ef141522
Publikováno v:
Biblioteca Digital de Teses e Dissertações da UFGUniversidade Federal de GoiásUFG.
Submitted by Liliane Ferreira (ljuvencia30@gmail.com) on 2018-07-17T13:45:19Z No. of bitstreams: 2 Tese - Leonardo Ravaglia Ferreira Gonçalves - 2018.pdf: 11284770 bytes, checksum: 846dd7e6423d34e412df82b0cbfd0999 (MD5) license_rdf: 0 bytes, checksu
Externí odkaz:
http://repositorio.bc.ufg.br/tede/handle/tede/8704