Name
Abstract | ||
|---|---|---|
In this study, a fast object detection algorithm based on binary deep convolution neural networks (CNNs) is proposed. Convolution kernels of different sizes are used to predict classes and bounding boxes of multi-scale objects directly in the last feature map of a deep CNN. In this way, rapid object detection with acceptable precision loss is achieved. In addition, binary quantisation for weight v... |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1049/trit.2018.1026 | CAAI Transactions on Intelligence Technology |
Keywords | Field | DocType |
object detection,convolution,neural nets | Object detection,Computer science,Convolution,Algorithm,Artificial neural network,Binary operation,Binary number,Bounding overwatch | Journal |
Volume | Issue | ISSN |
3 | 4 | 2468-6557 |
Citations | PageRank | References |
2 | 0.53 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Xingang Wang | 1 | 69 | 10.51 |
| Siyang Sun | 2 | 6 | 0.92 |
| Yingjie Yin | 3 | 43 | 4.72 |
| De Xu | 4 | 142 | 25.04 |
| Wenqi Wu | 5 | 89 | 15.21 |
| Qingyi Gu | 6 | 2 | 0.53 |