Adopting the YOLOv4 Architecture for Low-Latency Multispectral Pedestrian Detection in Autonomous Driving

Kamil Roszyk; Michał R. Nowicki; Piotr Skrzypczyński

doi:10.3390/s22031082

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Title

Adopting the YOLOv4 Architecture for Low-Latency Multispectral Pedestrian Detection in Autonomous Driving

Authors

Kamil Roszyk ^{[ S ]}
Michał R. Nowicki (WARiE) ^{[ 1 ][ 2.2 ][ P ]}
Piotr Skrzypczyński (WARiE) ^{[ 1 ][ 2.2 ][ P ]}

^{[ 1 ]} Instytut Robotyki i Inteligencji Maszynowej, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | ^{[ S ]} student | ^{[ P ]} employee

Scientific discipline (Law 2.0)

[2.2] Automation, electronics, electrical engineering and space technologies

Year of publication

2022

Published in

Sensors

Journal year: 2022 | Journal volume: vol. 22 | Journal number: iss. 3

Article type

scientific article

Publication language

english

Keywords

EN

pedestrian detection
multispectral fusion
deep learning
You Only Look Once
real-time

Date of online publication

30.01.2022

Pages (from - to)

1082-1 - 1082-21

DOI

10.3390/s22031082

URL

https://www.mdpi.com/1424-8220/22/3/1082

Comments

Article number: 1082

License type

CC BY (attribution alone)

Open Access Mode

open journal

Open Access Text Version

final published version

Release date

30.01.2022 (Date presumed)

Date of Open Access to the publication

at the time of publication

Full text of article

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Access level to full text

public

Ministry points / journal

100

Impact Factor

3,9

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