Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Authors: Sambit Mohapatra 1 ; Heinrich Gotzig 1 ; Senthil Yogamani 2 ; Stefan Milz 3 and Raoul Zöllner 4

Affiliations: 1 Valeo Bietigheim and Germany ; 2 Valeo Vision Systems and Ireland ; 3 Valeo Kronach and Germany ; 4 Heilbronn University and Germany

Keyword(s): Visual Perception, Efficient Networks, Automated Driving.

Abstract: Neural networks have become the standard model for various computer vision tasks in automated driving including semantic segmentation, moving object detection, depth estimation, visual odometry, etc. The main flavors of neural networks which are used commonly are convolutional (CNN) and recurrent (RNN). In spite of rapid progress in embedded processors, power consumption and cost is still a bottleneck. Spiking Neural Networks (SNNs) are gradually progressing to achieve low-power event-driven hardware architecture which has a potential for high efficiency. In this paper, we explore the role of deep spiking neural networks (SNN) for automated driving applications. We provide an overview of progress on SNN and argue how it can be a good fit for automated driving applications.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.138.190.225

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Mohapatra, S., Gotzig, H., Yogamani, S., Milz, S. and Zöllner, R. (2019). Exploring Deep Spiking Neural Networks for Automated Driving Applications. In Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP; ISBN 978-989-758-354-4; ISSN 2184-4321, SciTePress, pages 548-555. DOI: 10.5220/0007469405480555

@conference{visapp19,
author={Sambit Mohapatra and Heinrich Gotzig and Senthil Yogamani and Stefan Milz and Raoul Zöllner},
title={Exploring Deep Spiking Neural Networks for Automated Driving Applications},
booktitle={Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP},
year={2019},
pages={548-555},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0007469405480555},
isbn={978-989-758-354-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2019) - Volume 5: VISAPP
TI - Exploring Deep Spiking Neural Networks for Automated Driving Applications
SN - 978-989-758-354-4
IS - 2184-4321
AU - Mohapatra, S.
AU - Gotzig, H.
AU - Yogamani, S.
AU - Milz, S.
AU - Zöllner, R.
PY - 2019
SP - 548
EP - 555
DO - 10.5220/0007469405480555
PB - SciTePress

- Science and Technology Publications, Lda.
RESOURCES

Proceedings

Papers

Authors

Ontology

CONTACTS

Science and Technology Publications, Lda
Avenida de S. Francisco Xavier, Lote 7 Cv. C,
2900-616 Setúbal, Portugal.

Phone: +351 265 520 185 (National fixed network call)
Fax: +351 265 520 186
Email: info@scitepress.org

EXTERNAL LINKS

PRIMORIS

INSTICC

SCITEVENTS

CROSSREF

PROCEEDINGS SUBMITTED FOR INDEXATION BY:

dblp

Ei Compendex

SCOPUS

Semantic Scholar

Google Scholar

Microsoft Academic