Integrating Deep Learning-Based IoT and Fog Computing with Software-Defined Networking for Detecting Weapons in Video Surveillance Systems.

Fathy C, Saleh SN

DOI: 10.3390/s22145075
Published: 2022 Jul 6
Container: Sensors (Basel, Switzerland)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.3390/s22145075,
  title = {Integrating Deep Learning-Based IoT and Fog Computing with Software-Defined Networking for Detecting Weapons in Video Surveillance Systems.},
  author = {Fathy C and Saleh SN},
  year = {2022},
  journal = {Sensors (Basel, Switzerland)},
  doi = {10.3390/s22145075},
  url = {https://doi.org/10.3390/s22145075}
}

RIS

TY  - JOUR
TI  - Integrating Deep Learning-Based IoT and Fog Computing with Software-Defined Networking for Detecting Weapons in Video Surveillance Systems.
AU  - Fathy C
AU  - Saleh SN
PY  - 2022
JO  - Sensors (Basel, Switzerland)
DO  - 10.3390/s22145075
UR  - https://doi.org/10.3390/s22145075
ER  -

APA

C, F., & SN, S. (2022). Integrating Deep Learning-Based IoT and Fog Computing with Software-Defined Networking for Detecting Weapons in Video Surveillance Systems.. Sensors (Basel, Switzerland). https://doi.org/10.3390/s22145075

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pubmed · retrieved 2026-09-25T23:37:44.971Z