Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Kuangyuan Sun"'
Publikováno v:
IEEE Access, Vol 8, Pp 105455-105471 (2020)
Convolutional neural networks (CNNs) based deep learning algorithms require high data flow and computational intensity. For real-time industrial applications, they need to overcome challenges such as high data bandwidth requirement and power consumpt
Externí odkaz:
https://doaj.org/article/dcd2360477d3470883441cefc2b50db7
Publikováno v:
IEEE Access, Vol 8, Pp 105455-105471 (2020)
Convolutional neural networks (CNNs) based deep learning algorithms require high data flow and computational intensity. For real-time industrial applications, they need to overcome challenges such as high data bandwidth requirement and power consumpt
Publikováno v:
Electronics
Volume 9
Issue 5
Electronics, Vol 9, Iss 832, p 832 (2020)
Volume 9
Issue 5
Electronics, Vol 9, Iss 832, p 832 (2020)
Standard convolutional neural networks (CNNs) have large amounts of data redundancy, and the same accuracy can be obtained even in lower bit weights instead of floating-point representation. Most CNNs have to be developed and executed on high-end GPU
Publikováno v:
2018 International Conference on Electronics, Information, and Communication (ICEIC).
One of the major challenges in these days is "How can we implement up-to-date object detection algorithm in the heterogeneous system?" As in 2012 Visual Object Classes Challenge (VOC)[1] have achieved a very satisfied performance of deep learning neu
Publikováno v:
ISOCC
Convolutional Neural Network (CNN) is a powerful tool in machine learning area. However, the convolution computation is time-consuming, which limited the application on embedded system. In this paper, we introduce a parallel convolution acceleration
Publikováno v:
ISOCC
Deep learning neural network is very powerful to deal with signal processing, computer vision and many other recognition problems since its high accuracy. The CUDA based framework is a mainstream in deep learning models. In this paper, we present Ope