Name
Abstract | ||
|---|---|---|
In the past few years, the demand for real-time hardware implementations of deep neural networks (DNNs), especially convolutional neural networks (CNNs), has dramatically increased, thanks to their excellent performance on a wide range of recognition and classification tasks. When considering real-time action recognition and video/image classification systems, latency is of paramount importance. T... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1109/TCSI.2017.2757036 | IEEE Transactions on Circuits and Systems I: Regular Papers |
Keywords | Field | DocType |
Convolution,Neurons,Computer architecture,Complexity theory,Neural networks,Hardware,Three-dimensional displays | Data set,Latency (engineering),Computer science,Convolutional neural network,Electronic engineering,Artificial intelligence,Contextual image classification,Artificial neural network,Computer engineering,Convolution,CMOS,Machine learning,Computational complexity theory | Journal |
Volume | Issue | ISSN |
65 | 4 | 1549-8328 |
Citations | PageRank | References |
4 | 0.45 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Arash Ardakani | 1 | 33 | 8.42 |
| Carlo Condo | 2 | 132 | 21.40 |
| Mehdi Ahmadi | 3 | 5 | 0.81 |
| Warren J. Gross | 4 | 7 | 2.27 |