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English Information

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Authors
# Name
1 Fábio Luiz Júnior(fabioluiz@ime.eb.br)
2 Bruno Eduardo de Oliveira Carvalho(bruno.carvalho@ime.eb.br)
3 Julio Cesar Santana da Rosa Filho(jcesar@ime.eb.br)
4 Paulo Fernando Ferreira Rosa(rpaulo@ime.eb.br)
5 Julio Cesar Duarte(duarte@ime.eb.br)

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Reference
# Reference
1 Gencoglu, O., Virtanen, T., and Huttunen, H. (2014). Recognition of acoustic events using deep neural networks. In 2014 22nd European Signal Processing Conference (EUSIPCO), pages 506–510, Lisbon, Portugal. IEEE.
2 Gray, R. (2017). Gunfire audio opens new front in crime-fighting. BBC News.
3 Khan, S., Divakaran, A., and Sawhney, H. S. (2010). Weapon identification across varying acoustic conditions using an exemplar embedding approach. In Sensors, and Command, Control, Communications, and Intelligence (C3I) Technologies for Homeland Security and Homeland Defense IX, volume 7666, pages 494–501, Bellingham, WA, USA. SPIE.
4 Kiktova, E., Lojka, M., Pleva, M., Juhar, J., and Cizmar, A. (2015). Gun type recognition from gunshot audio recordings. In 3rd International Workshop on Biometrics and Forensics (IWBF 2015), pages 1–6, Gjøvik, Norway. IEEE.
5 Lilien, R. (2018). Development of Computational Methods for the Audio Analysis of Gunshots. Cadre Research Lab, Chicago, IL.
6 Piczak, K. J. (2015). ESC: Dataset for environmental sound classification. In Proceedings of the 23rd ACM International Conference on Multimedia, MM '15, pages 1015–1018, New York, NY, USA. Association for Computing Machinery.
7 Raponi, S., Oligeri, G., and Ali, I. M. (2022). Sound of guns: Digital forensics of gun audio samples meets artificial intelligence. Multimedia Tools and Applications, 81(21):30387–30412.
8 Stephens, S. (2023). Knightscope announces automated gunshot detection. https://www.businesswire.com/news/home/20230714391246/en/Knightscope-Announces-Automated-Gunshot-Detection