loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Hamed H. Aghdam ; Elnaz J. Heravi and Domenec Puig

Affiliation: Rovira i Virgili University, Spain

Keyword(s): Image Restoration, Image Denoising, Road Understanding, Traffic Sign Classification, Pedestrian Detection.

Related Ontology Subjects/Areas/Topics: Computer Vision, Visualization and Computer Graphics ; Features Extraction ; Image and Video Analysis

Abstract: One of the challenges in problems related to road understanding is to deal with noisy images. Especially, recent studies have revealed that ConvNets are sensitive to small perturbations in the input. One solution for dealing with this problem is to generate many noisy images during training a ConvNet. However, this approach is very costly and it is not a certain solution. In this paper, we propose an objective function regularized by the local Lipschitz constant and train a ReLU layer for restoring noisy images. Our experiments on the GTSRB and the Caltech-Pedestrian datasets show that this lightweight approach not only increases the accuracy of the classification ConvNets on the clean datasets but it also increases the stability of the ConvNets against noise. Comparing our method with similar approaches shows that it produces more stable ConvNets while it is computationally similar or more efficient than these methods.

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 3.138.118.194

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:
Aghdam, H.; Heravi, E. and Puig, D. (2017). Increasing the Stability of CNNs using a Denoising Layer Regularized by Local Lipschitz Constant in Road Understanding Problems. In Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP; ISBN 978-989-758-226-4; ISSN 2184-4321, SciTePress, pages 218-225. DOI: 10.5220/0006123602180225

@conference{visapp17,
author={Hamed H. Aghdam. and Elnaz J. Heravi. and Domenec Puig.},
title={Increasing the Stability of CNNs using a Denoising Layer Regularized by Local Lipschitz Constant in Road Understanding Problems},
booktitle={Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP},
year={2017},
pages={218-225},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006123602180225},
isbn={978-989-758-226-4},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2017) - Volume 5: VISAPP
TI - Increasing the Stability of CNNs using a Denoising Layer Regularized by Local Lipschitz Constant in Road Understanding Problems
SN - 978-989-758-226-4
IS - 2184-4321
AU - Aghdam, H.
AU - Heravi, E.
AU - Puig, D.
PY - 2017
SP - 218
EP - 225
DO - 10.5220/0006123602180225
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