A Firearm Identification System Based on Neural Network
Document Type
Conference Proceeding
Publisher
Springer
Faculty
Faculty of Computing, Health and Science
School
School of Computer and Information Science
RAS ID
2577
Abstract
In this paper, a Firearm Identification system based on Self-Organizing Feature Map (SOFM) neural network is proposed. We focus on the cartridge case identification of rim-firing mechanism. Experiments show that the model proposed has high performance and robustness by integrating the SOFM neural network and the decision-making strategy. This model will also make a significant contribution towards the further processing, such as the more efficient and precise identification of cartridge cases by combination with more characteristics on cartridge cases images.
DOI
10.1007/978-3-540-24581-0_27
Comments
Kong, J., Li, D., & Watson, A. C. (2003). A firearm identification system based on neural network. Proceedings of 16th Australian Conference on AI. AI 2003: Advances in Artificial Intelligence. (pp. 315-326). Berlin, Germany: Springer. Available here