Name
Abstract | ||
|---|---|---|
3D convolutional neural networks (CNNs) are gaining increasing popularity in the area of video-based action/activity analysis. Compared to 2D convolutions that share the filters in a 2D spatial domain, 3D convolutions further reuse filters in the temporal dimension to capture temporal-domain features in the video. How to exploit the data locality in the temporal dimension directly impacts the ener... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCAD.2020.3011042 | IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems |
Keywords | DocType | Volume |
Three-dimensional displays,Two dimensional displays,Arrays,Feature extraction,System-on-chip,Redundancy | Journal | 40 |
Issue | ISSN | Citations |
5 | 0278-0070 | 1 |
PageRank | References | Authors |
0.40 | 0 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ying Wang | 1 | 276 | 55.61 |
| Yongchen Wang | 2 | 1 | 0.73 |
| Cong Shi | 3 | 489 | 40.60 |
| Long Cheng | 4 | 91 | 16.99 |
| Huawei Li | 5 | 417 | 56.32 |
| Xinrong Li | 6 | 1266 | 157.76 |