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Valentim, S., Fonseca, T., Ferreira, J., Brandão, T., Ribeiro, R. & Nae, S. (2021). Gun model classification based on fired cartridge case head images with siamese networks. In Abraham, A., Gandhi, N., Hanne, T., Hong, T.-P., Nogueira Rios, T., and Ding, W. (Ed.), Intelligent Systems Design and Applications. Lecture Notes in Networks and Systems. (pp. 1281-1291). Virtual, Online: Springer Cham.

S. A. Valentim et al.,  "Gun model classification based on fired cartridge case head images with siamese networks", in Intelligent Systems Design and Applications. Lecture Notes in Networks and Systems, Abraham, A., Gandhi, N., Hanne, T., Hong, T.-P., Nogueira Rios, T., and Ding, W., Ed., Virtual, Online, Springer Cham, 2021, vol. 418, pp. 1281-1291

@inproceedings{valentim2021_1732212020866,
	author = "Valentim, S. and Fonseca, T. and Ferreira, J. and Brandão, T. and Ribeiro, R. and Nae, S.",
	title = "Gun model classification based on fired cartridge case head images with siamese networks",
	booktitle = "Intelligent Systems Design and Applications. Lecture Notes in Networks and Systems",
	year = "2021",
	editor = "Abraham, A., Gandhi, N., Hanne, T., Hong, T.-P., Nogueira Rios, T., and Ding, W.",
	volume = "418",
	number = "",
	series = "",
	doi = "10.1007/978-3-030-96308-8_119",
	pages = "1281-1291",
	publisher = "Springer Cham",
	address = "Virtual, Online",
	organization = "",
	url = "https://link.springer.com/book/10.1007/978-3-030-96308-8"
}

TY  - CPAPER
TI  - Gun model classification based on fired cartridge case head images with siamese networks
T2  - Intelligent Systems Design and Applications. Lecture Notes in Networks and Systems
VL  - 418
AU  - Valentim, S.
AU  - Fonseca, T.
AU  - Ferreira, J.
AU  - Brandão, T.
AU  - Ribeiro, R.
AU  - Nae, S.
PY  - 2021
SP  - 1281-1291
SN  - 2367-3370
DO  - 10.1007/978-3-030-96308-8_119
CY  - Virtual, Online
UR  - https://link.springer.com/book/10.1007/978-3-030-96308-8
AB  - The identification of the firearm model that triggered the firing of a bullet is an important forensic information that, historically, has been done by trained examiners through visual inspection using microscopes. This is an extensive and very time-consuming process that requires the examiners to be trained to identify and compare the fired cartridges. This paper proposes an automated objective method for binary classifying pairs of fired cartridge head images as belonging to the same or different classes, using siamese neural networks (SNNs). With this technique, an accuracy of up to 70% was reached by using firing pin mark images as the input of the SNN. For the training and optimization of the network this paper also analyses and presents different image preprocessing approaches.
ER  -