Zobrazeno 1 - 10
of 250
pro vyhledávání: '"neural network design"'
Autor:
Saeid Safaei, Zerotti Woods, Khaled Rasheed, Thiab R. Taha, Vahid Safaei, Juan B. Gutierrez, Hamid R. Arabnia
Publikováno v:
IEEE Access, Vol 12, Pp 73363-73375 (2024)
Deep learning techniques have demonstrated significant capabilities across numerous applications, with deep neural networks (DNNs) showing promising results. However, training these networks efficiently, especially when determining the most suitable
Externí odkaz:
https://doaj.org/article/bc878b86af9940c382aabfe5c08372f1
Publikováno v:
IEEE Open Journal of the Communications Society, Vol 5, Pp 2287-2301 (2024)
Radio environment maps (REMs) have been established as an important tool in spectrum occupancy characterization toward more efficient coverage planning and design of resource allocation algorithms. The utilization of deep learning (DL) techniques for
Externí odkaz:
https://doaj.org/article/93ee6549a8fd4983ab8422d59448111f
Publikováno v:
Alexandria Engineering Journal, Vol 81, Iss , Pp 55-63 (2023)
The architecture of deep neural networks is commonly determined via trial and error, resulting in inefficiency and a lack of architecture interpretability. Recent research shows that numerical solutions of ordinary differential equations have demonst
Externí odkaz:
https://doaj.org/article/055f205465d045f3b83047c368c008ee
Publikováno v:
Machines, Vol 12, Iss 8, p 574 (2024)
As we move into the next stages of the technological revolution, artificial intelligence (AI) that is explainable and sustainable is becoming a key goal for researchers across multiple domains. Leveraging the concept of functional connectivity (FC) i
Externí odkaz:
https://doaj.org/article/48e5826e0afe4fcea0f536f86359d30e
Autor:
WU Yanchen, WANG Yingmin
Publikováno v:
Xibei Gongye Daxue Xuebao, Vol 40, Iss 1, Pp 40-46 (2022)
In the face of the challenges in the field of marine engineering applications in the new era, the goal of automation, high efficiency and accuracy can be achieved by using deep learning-based neural networks in hydroacoustic engineering. However, in
Externí odkaz:
https://doaj.org/article/2a1de612dc9c4c7f869d07bd1d08dfb1
Akademický článek
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Publikováno v:
Applied Sciences, Vol 13, Iss 12, p 7079 (2023)
The primary objective of this study is to provide an extensive review of deep learning techniques for medical image recognition, highlighting their potential for improving diagnostic accuracy and efficiency. We systematically organize the paper by fi
Externí odkaz:
https://doaj.org/article/5a526df3bc834770ab686c238f809059
Publikováno v:
IEEE Access, Vol 9, Pp 68008-68016 (2021)
It is no longer an option but a necessity to enhance the efficiency of deep learning models regarding energy consumption, learning time, and model size as the computational burden on deep neural networks increases. To improve the efficiency of deep l
Externí odkaz:
https://doaj.org/article/55546893818a4be79f1380a26d03b689
Publikováno v:
TEM Journal. 9(4):1320-1329
Externí odkaz:
https://www.ceeol.com/search/article-detail?id=913585
Autor:
Eunhui Kim, Kyong-Ha Lee
Publikováno v:
IEEE Access, Vol 8, Pp 207683-207690 (2020)
Deep neural networks (DNN) have been applied to numerous artificial-intelligence applications because of their remarkable accuracy. However, computational requirements for deep neural networks are recently skyrocketing far beyond the Moore's Law. In
Externí odkaz:
https://doaj.org/article/465fa53d72214d2b9d5365361f5883a4