Title

A Firearm Identification System Based on Neural Network

Document Type

Conference Proceeding

Publisher

Springer

Faculty

Computing, Health and Science

School

Computer and Information Science

RAS ID

2577

Comments

This article was originally published as: 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. Original article available here

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

 

Link to publisher version (DOI)

10.1007/978-3-540-24581-0_27