Detail publikace

Gunshot detection using convolutional neural networks

BAJZÍK, J. PŘINOSIL, J. KONIAR, D.

Originální název

Gunshot detection using convolutional neural networks

Anglický název

Gunshot detection using convolutional neural networks

Jazyk

en

Originální abstrakt

The main paper deals with the analysis of the methods of signal processing and events recognition in the audio signal and the implementation of the selected method in real use. Recognized events are gunshots mixed with a background sound such as traffic noise, human voice, animal sounds and other forms of environmental sounds. The proposed algorithm adapted for explosion detection can be used as part of a security system for monitoring depots or places dedicated to storing dangerous materials. For events classification and class recognition, the freely available machine learning frameworks TensorFlow and Keras are used.

Anglický abstrakt

The main paper deals with the analysis of the methods of signal processing and events recognition in the audio signal and the implementation of the selected method in real use. Recognized events are gunshots mixed with a background sound such as traffic noise, human voice, animal sounds and other forms of environmental sounds. The proposed algorithm adapted for explosion detection can be used as part of a security system for monitoring depots or places dedicated to storing dangerous materials. For events classification and class recognition, the freely available machine learning frameworks TensorFlow and Keras are used.

Dokumenty

BibTex


@inproceedings{BUT165911,
  author="Jakub {Bajzík} and Jiří {Přinosil} and Dušan {Koniar}",
  title="Gunshot detection using convolutional neural networks",
  annote="The main paper deals with the analysis of the methods of signal processing and events recognition in the audio signal and the implementation of the selected method in real use. Recognized events are gunshots mixed with a background sound such as traffic noise, human voice, animal sounds and other forms of environmental sounds. The proposed algorithm adapted for explosion detection can be used as part of a security system for monitoring depots or places dedicated to storing dangerous materials. For events classification and class recognition, the freely available machine learning frameworks TensorFlow and Keras are used.",
  address="Institute of Electrical and Electronics Engineers Inc.",
  booktitle="24th International Conference Electronics, ELECTRONICS 2020",
  chapter="165911",
  doi="10.1109/IEEECONF49502.2020.9141621",
  howpublished="online",
  institution="Institute of Electrical and Electronics Engineers Inc.",
  year="2020",
  month="june",
  pages="1--5",
  publisher="Institute of Electrical and Electronics Engineers Inc.",
  type="conference paper"
}