Abstract
This paper investigates whether advanced neural network techniques can be applied to the detection and identification of typical targets in the context of land warfare. We collected 13 typical targets and built a detection data set. Based on the Faster R-CNN framework, we improve the detection accuracy by two ways. First, we design a neural network model with strong local modeling capabilities. Second, we combine middle layers and the last layer of feature maps as the detection features to enhance the detection ability and improve the detection accuracy.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 4313-4318 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509046560 |
| DOIs | |
| Publication status | Published - 12 Jul 2017 |
| Event | 29th Chinese Control and Decision Conference, CCDC 2017 - Chongqing, China Duration: 28 May 2017 → 30 May 2017 |
Publication series
| Name | Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017 |
|---|
Conference
| Conference | 29th Chinese Control and Decision Conference, CCDC 2017 |
|---|---|
| Country/Territory | China |
| City | Chongqing |
| Period | 28/05/17 → 30/05/17 |
Keywords
- Convolutional Neural Network
- Deep Learning
- Local Modeling Capability
- Object Detection
Fingerprint
Dive into the research topics of 'The detection of typical targets under the background of land war'. Together they form a unique fingerprint.Cite this
Wu, X., Chen, W., & Qin, Y. (2017). The detection of typical targets under the background of land war. In Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017 (pp. 4313-4318). Article 7979256 (Proceedings of the 29th Chinese Control and Decision Conference, CCDC 2017). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/CCDC.2017.7979256