Zobrazeno 1 - 10
of 12
pro vyhledávání: '"Emilio Rapuano"'
Publikováno v:
IEEE Access, Vol 11, Pp 32759-32775 (2023)
In recent years, Convolutional Neural Networks (CNNs) have demonstrated outstanding results in several emerging classification tasks. The high-quality predictions are often achieved with computationally intensive workloads that hinder the hardware ac
Externí odkaz:
https://doaj.org/article/b101ecdca8304b22b85d6d16493d809d
Publikováno v:
International Journal of Reconfigurable Computing, Vol 2019 (2019)
During the last years, convolutional neural networks have been used for different applications, thanks to their potentiality to carry out tasks by using a reduced number of parameters when compared with other deep learning approaches. However, power
Externí odkaz:
https://doaj.org/article/a5ebc8fe8f2742efa49f2c4da9cd49ab
Autor:
Emilio Rapuano, Gabriele Meoni, Tommaso Pacini, Gianmarco Dinelli, Gianluca Furano, Gianluca Giuffrida, Luca Fanucci
Publikováno v:
Remote Sensing, Vol 13, Iss 8, p 1518 (2021)
In recent years, research in the space community has shown a growing interest in Artificial Intelligence (AI), mostly driven by systems miniaturization and commercial competition. In particular, the application of Deep Learning (DL) techniques on boa
Externí odkaz:
https://doaj.org/article/5452cd2b05874e2c8294f1ef6fe9f828
Publikováno v:
Lecture Notes in Electrical Engineering ISBN: 9783030954970
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a5ed5d1a6a720ea796e3d59ad961a93d
https://doi.org/10.1007/978-3-030-95498-7_26
https://doi.org/10.1007/978-3-030-95498-7_26
Publikováno v:
Computational Intelligence and Neuroscience.
Recurrent Neural Networks (RNNs) have become important tools for tasks such as speech recognition, text generation, or natural language processing. However, their inference may involve up to billions of operations and their large number of parameters
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6471d259eba05ebb9dc70138b69b7db9
In the last years, Convolutional Neural networks (CNNs) found applications in many fields from computer vision to speech recognition, showing outstanding results in terms of accuracy. Field Programmable Gate Arrays (FPGAs) proved to be a promising pl
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1dfeabd69692688c3276fb77018b7ecf
http://hdl.handle.net/11568/1066074
http://hdl.handle.net/11568/1066074
Publikováno v:
ISCAS
Convolution Neural Networks are a class of deep neural networks commonly used in audio and video elaborations. Their implementation on the edge represents a complex task due to the limited computational power and low power consumption requirement tha
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5beaba7575b51301c04c5aac7ed4edb3
http://hdl.handle.net/11568/1066406
http://hdl.handle.net/11568/1066406
Publikováno v:
Electronics
Volume 10
Issue 20
Electronics, Vol 10, Iss 2514, p 2514 (2021)
Volume 10
Issue 20
Electronics, Vol 10, Iss 2514, p 2514 (2021)
In recent years, FPGAs have demonstrated remarkable performance and contained power consumption for the on-the-edge inference of Convolutional Neural Networks. One of the main challenges in implementing this class of algorithms on board an FPGA is re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7f9dc8bcd8022fc7b23dd4154ebbf83
https://doi.org/10.3390/electronics10202514
https://doi.org/10.3390/electronics10202514
Publikováno v:
International Journal of Reconfigurable Computing, Vol 2019 (2019)
During the last years, convolutional neural networks have been used for different applications, thanks to their potentiality to carry out tasks by using a reduced number of parameters when compared with other deep learning approaches. However, power
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0f906fd2fd2467b3b48f8d9df8e4accf
https://doaj.org/article/a5ebc8fe8f2742efa49f2c4da9cd49ab
https://doaj.org/article/a5ebc8fe8f2742efa49f2c4da9cd49ab
Autor:
Gianmarco Dinelli, Gianluca Furano, Tommaso Pacini, Luca Fanucci, Emilio Rapuano, Gianluca Giuffrida, Gabriele Meoni
Publikováno v:
Remote Sensing, Vol 13, Iss 1518, p 1518 (2021)
Remote Sensing; Volume 13; Issue 8; Pages: 1518
Remote Sensing; Volume 13; Issue 8; Pages: 1518
In recent years, research in the space community has shown a growing interest in Artificial Intelligence (AI), mostly driven by systems miniaturization and commercial competition. In particular, the application of Deep Learning (DL) techniques on boa
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d84e6072737583d62c8cd2587d2ab0e0
https://doi.org/10.3390/rs13081518
https://doi.org/10.3390/rs13081518