On the Complexity of Object Detection on Real-world Public Transportation Images for Social Distancing Measurement-Reference-Cited by-同舟云学术

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On the Complexity of Object Detection on Real-world Public Transportation Images for Social Distancing Measurement

Published:2022-07-18 Issue: Volume: Page:
ISSN:
Container-title:2022 International Joint Conference on Neural Networks (IJCNN)
language:
Short-container-title:

Author:

Nik Aznan Nik Khadijah¹,Brennan John²,Bell Daniel³,Jonczyk Jennine³,Watson Paul⁴

Affiliation:

1. Newcastle University,Research Software Engineering,Newcastle,UK

2. National Innovation Centre for Data, Newcastle University,Newcastle,UK

3. Newcastle University,Urban Observatory,Newcastle,UK

4. School of Computing, Newcastle University,Newcastle,UK

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9891857/9889787/09891955.pdf?arnumber=9891955

Reference28 articles.

1. How can airborne transmission of COVID-19 indoors be minimised?

2. Object detection in 20 years: A survey;zou;ArXiv Preprint,2019

3. Deep Learning for Generic Object Detection: A Survey

4. Microsoft coco: Common objects in context;lin;European Conference on Computer Vision,0

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