Zobrazeno 1 - 10
of 184
pro vyhledávání: '"Felipe M. G. França"'
Autor:
Zachary Susskind, Aman Arora, Alan T. L. Bacellar, Diego L. C. Dutra, Igor D. S. Miranda, Mauricio Breternitz, Priscila M. V. Lima, Felipe M. G. França, Lizy K. John
Publikováno v:
Proceedings of the 2023 ACM/SIGDA International Symposium on Field Programmable Gate Arrays.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0c864efcbbedb4195b7e3ae3fbe3aef
https://doi.org/10.1145/3543622.3573140
https://doi.org/10.1145/3543622.3573140
Autor:
Zachary Susskind, Aman Arora, Igor D. S. Miranda, Luis A. Q. Villon, Rafael F. Katopodis, Leandro S. de Araújo, Diego L. C. Dutra, Priscila M. V. Lima, Felipe M. G. França, Mauricio Breternitz, Lizy K. John
Publikováno v:
Proceedings of the International Conference on Parallel Architectures and Compilation Techniques.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ce5b2474e7215f99b8eb59d7a74501b8
https://doi.org/10.1145/3559009.3569680
https://doi.org/10.1145/3559009.3569680
Autor:
Victor C. Ferreira, Vinay C. Patil, Felipe M. G. França, Brunno F. Goldstein, Sandip Kundu, Alexandre S. Nery
Publikováno v:
IEEE Journal on Emerging and Selected Topics in Circuits and Systems. 11:267-277
Training accurate deep learning (DL) models require large amounts of training data, significant work in labeling the data, considerable computing resources, and substantial domain expertise. In short, they are expensive to develop. Hence, protecting
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4ec8f8d0c4d0c4888de88a1b75dcb886
https://doi.org/10.1109/jetcas.2021.3076151
https://doi.org/10.1109/jetcas.2021.3076151
Publikováno v:
IEEE Transactions on Emerging Topics in Computing. 9:44-54
Dynamic dataflow scheduling enables effective exploitation of concurrency while making parallel programming easier. To this end, analyzing the inherent degree of concurrency available in dataflow graphs is an important task, since it may aid compiler
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b2b3c895e3b52b4c4f4d1870447a5b92
https://doi.org/10.1109/tetc.2018.2799078
https://doi.org/10.1109/tetc.2018.2799078
Autor:
Luidi Simonetti, Carlos E. Marciano, Luerbio Faria, Felipe M. G. França, Gladstone M. Arantes, Abilio Lucena
Publikováno v:
Networks. 77:520-537
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d389a3bcfcbf892e5d9027b3e2c995c8
https://doi.org/10.1002/net.22014
https://doi.org/10.1002/net.22014
Autor:
Daniel Sadoc Menasche, Priscila M. V. Lima, Letícia Dias Verona, Fabricio Firmino, Felipe M. G. França, Sandip Kundu, Wouter Caarls, Leandro Santiago, Fabio Rangel, Mauricio Breternitz
Publikováno v:
Neurocomputing. 416:292-304
Weightless Neural Networks (WNNs) are Artificial Neural Networks based on RAM memory broadly explored as solution for pattern recognition applications. Memory-oriented solutions for pattern recognition are typically very simple, and can be easily imp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::694036284c4a30083fb748e2d1eb8f49
https://doi.org/10.1016/j.neucom.2020.01.115
https://doi.org/10.1016/j.neucom.2020.01.115
Autor:
Priscila M. V. Lima, Gabriel P. Guarisa, Aluizio Lima Filho, Lucca M. Felix, Luiz Felipe Ramalho de Oliveira, Felipe M. G. França, Leopoldo Lusquino Filho
Publikováno v:
Neurocomputing. 416:280-291
This paper explores two new weightless neural network models, Regression WiSARD and ClusRegression WiSARD, in the challenging task of predicting the total palm oil production of a set of 28 (twenty eight) differently located sites under different cli
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::567e7952be6ca7772aab5a4167f91bca
https://doi.org/10.1016/j.neucom.2019.12.134
https://doi.org/10.1016/j.neucom.2019.12.134
Autor:
Priscila M. V. Lima, Siavash Rezaei, Brunno F. Goldstein, Hossein Bobarshad, Jaeyoung Do, Mahdi Torabzadehkashi, Min Soo Kim, Diego Fonseca Pereira de Souza, Felipe M. G. França, Leandro Santiago, Victor C. Ferreira, Vladimir Alves, Ali Heydarigorji
Publikováno v:
ACM Transactions on Storage. 16:1-37
The growing volume of data produced continuously in the Cloud and at the Edge poses significant challenges for large-scale AI applications to extract and learn useful information from the data in a timely and efficient way. The goal of this article i
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b5ad2430d704933cb2f02964b099e1b8
https://doi.org/10.1145/3415580
https://doi.org/10.1145/3415580
Autor:
Luis F. M. de Moraes, Fabio H. Silva, Egberto A. R. de Oliveira, José Ferreira de Rezende, Rui R. Mello, Felipe M. G. França, Evandro L. C. Macedo, Flavia C. Delicato
Publikováno v:
Journal of Communications and Networks. 21:444-457
Internet of Things (IoT) has gained increasing visibility among emerging technologies and undoubtedly changing our daily life. Its adoption is strengthened by the growth of connected devices (things) as shown in recent statistics. However, as the num
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::50ef4e0bb048596dac3639e581ee4add
https://doi.org/10.1109/jcn.2019.000048
https://doi.org/10.1109/jcn.2019.000048
Publikováno v:
Neural Computation. 31:176-207
The Wilkie, Stonham, and Aleksander recognition device (WiSARD) [Formula: see text]-tuple classifier is a multiclass weightless neural network capable of learning a given pattern in a single step. Its architecture is determined by the number of class
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::41c7ae80c6d9492ab10a7c445cdcd2d0
https://doi.org/10.1162/neco_a_01149
https://doi.org/10.1162/neco_a_01149