Combating illegal hunting of mammals using SED
Abstract
In order to combat illegal hunting activities, there are approa- ches that use machine learning to formulate better patrol strategies. As a complementary way, we propose a model using neural networks for the de- tection of potentially illegal activities, through the processing of the sound captured in regions where there is inhabiting fauna.
Keywords:
Machine Learning, Illegal hunting, sound processing
References
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Xu, L., Bondi, E., Fang, F., Perrault, A., Wang, K., and Tambe, M. (2020a). Dual- Mandate Patrols: Multi-Armed Bandits for Green Security. arXiv:2009.06560 [cs, stat]. arXiv: 2009.06560.
Xu, L., Gholami, S., McCarthy, S., Dilkina, B., Plumptre, A., Tambe, M., Singh, R., Nsubuga, M., Mabonga, J., Driciru, M., Wanyama, F., Rwetsiba, A., Okello, T., and Enyel, E. (2020b). Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations (Short Version). In 2020 IEEE 36th International Conference on Data Engineering (ICDE), pages 1898–1901, Dallas, TX, USA. IEEE.
Ardila, R., Branson, M., Davis, K., Henretty, M., Kohler, M., Meyer, J., Morais, R., Saunders, L., Tyers, F. M., and Weber, G. (2020). Common voice: A massively multilingual speech corpus.
Chan, T. K. and Chin, C. S. (2020). A comprehensive review of polyphonic sound event detection. IEEE Access, 8:103339–103373.
Dogan, S. (2021). A new fractal h-tree pattern based gun model identification method using gunshot audios. Applied Acoustics, 177:107916.
Drossos, K., Mimilakis, S. I., Gharib, S., Li, Y., and Virtanen, T. (2020). Sound Event Detection with Depthwise Separable and Dilated Convolutions. In 2020 International Joint Conference on Neural Networks (IJCNN), pages 1–7, Glasgow, United Kingdom. IEEE.
Ferraro, A., Bogdanov, D., Jeon, J. H., Yoon, J., and Serra, X. (2019). Music auto-tagging using cnns and mel-spectrograms with reduced frequency and time resolution. CoRR, abs/1911.04824.
Fulzele, V., Kulkarni, Y., and Aras, S. (2020). Conservation of wildlife from poaching by using sound detection and machine learning. INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY.
Henrique, D. (2021). Human animal hunting audio dataset.
Ismail Fawaz, H., Lucas, B., Forestier, G., Pelletier, C., Schmidt, D. F., Weber, J., Webb, G. I., Idoumghar, L., Muller, P.-A., and Petitjean, F. (2020). Inception- time: Finding alexnet for time series classification. Data Mining and Knowledge Discovery, 34(6):1936–1962.
Liang, J., Aronson, J. D., and Hauptmann, A. (2019). Technical Report of the Video Event Reconstruction and Analysis (VERA) System – Shooter Localization, Models, Interface, and Beyond. arXiv:1905.13313 [cs]. arXiv: 1905.13313.
Lilien, R. (2018). Development of computational methods for the audio analysis of gunshots.
Piczak, K. J. (2015). ESC: Dataset for Environmental Sound Classification. In Proceedings of the 23rd Annual ACM Conference on Multimedia, pages 1015– 1018. ACM Press.
Purwins, H., Li, B., Virtanen, T., Schl ̈uter, J., Chang, S., and Sainath, T. N. (2019). Deep learning for audio signal processing. CoRR, abs/1905.00078.
Salamon, J., Jacoby, C., and Bello, J. P. (2014). A dataset and taxonomy for urban sound research. In 22nd ACM International Conference on Multimedia (ACMMM’14), pages 1041–1044, Orlando, FL, USA.
Xu, L., Bondi, E., Fang, F., Perrault, A., Wang, K., and Tambe, M. (2020a). Dual- Mandate Patrols: Multi-Armed Bandits for Green Security. arXiv:2009.06560 [cs, stat]. arXiv: 2009.06560.
Xu, L., Gholami, S., McCarthy, S., Dilkina, B., Plumptre, A., Tambe, M., Singh, R., Nsubuga, M., Mabonga, J., Driciru, M., Wanyama, F., Rwetsiba, A., Okello, T., and Enyel, E. (2020b). Stay Ahead of Poachers: Illegal Wildlife Poaching Prediction and Patrol Planning Under Uncertainty with Field Test Evaluations (Short Version). In 2020 IEEE 36th International Conference on Data Engineering (ICDE), pages 1898–1901, Dallas, TX, USA. IEEE.
Published
2022-06-01
How to Cite
HENRIQUE, Davi F.; BLUME, Mariana M.; RIVA, Aline Duarte.
Combating illegal hunting of mammals using SED. In: REGIONAL SCHOOL ON COMPUTING OF RIO GRANDE DO SUL (ERCOMP-RS), 2. , 2022, Canoas.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2022
.
p. 56-63.
DOI: https://doi.org/10.5753/ercomprs.2022.20406.
