Abstract
Recently, intellectuahzafion of weapon equipment has become a development trend. Convolufional neural network (CNN) has demonstrated extraordinary performance in image classification, target detection and tracking tasks. Therefore, applying CNN algorithm to weapon equipment can improve the ability of object identification and anti-interference in complex environment. In this paper, a design method of FPGA-based convolufional neural network model is presented, and the function is verified on the Xihnx Virtex-7 series FPGA. The model is reconfigurable and flexible, which has strong transplant a-bihty and wide application range.
| Translated title of the contribution | Design of FPGA-Based Convolutional Neural Network Model |
|---|---|
| Original language | Chinese (Traditional) |
| Pages (from-to) | 15-20 |
| Number of pages | 6 |
| Journal | Aero Weaponry |
| Volume | 26 |
| Issue number | 2 |
| DOIs | |
| State | Published - 30 Apr 2019 |