loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Grigorios Kalliatakis 1 ; Shoaib Ehsan 1 ; Maria Fasli 1 ; Ales Leonardis 2 ; Juergen Gall 3 and Klaus D. McDonald-Maier 1

Affiliations: 1 University of Essex, United Kingdom ; 2 University of Birmingham, United Kingdom ; 3 University of Bonn, Germany

Keyword(s): Convolutional Neural Networks, Deep Representation, Human Rights Violations Recognition.

Abstract: After setting the performance benchmarks for image, video, speech and audio processing, deep convolutional networks have been core to the greatest advances in image recognition tasks in recent times. This raises the question of whether there are any benefit in targeting these remarkable deep architectures with the unattempted task of recognising human rights violations through digital images. Under this perspective, we introduce a new, well-sampled human rights-centric dataset called Human Rights Understanding (HRUN). We conduct a rigorous evaluation on a common ground by combining this dataset with different state-of-the-art deep convolutional architectures in order to achieve recognition of human rights violations. Experimental results on the HRUN dataset have shown that the best performing CNN architectures can achieve up to 88.10% mean average precision. Additionally, our experiments demonstrate that increasing the size of the training samples is crucial for achieving an improvem ent on mean average precision principally when utilising very deep networks. (More)

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 18.222.56.251

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:
Kalliatakis, G.; Ehsan, S.; Fasli, M.; Leonardis, A.; Gall, J. and McDonald-Maier, K. (2017). Detection of Human Rights Violations in Images: Can Convolutional Neural Networks Help?. 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 289-296. DOI: 10.5220/0006133902890296

@conference{visapp17,
author={Grigorios Kalliatakis. and Shoaib Ehsan. and Maria Fasli. and Ales Leonardis. and Juergen Gall. and Klaus D. McDonald{-}Maier.},
title={Detection of Human Rights Violations in Images: Can Convolutional Neural Networks Help?},
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={289-296},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006133902890296},
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 - Detection of Human Rights Violations in Images: Can Convolutional Neural Networks Help?
SN - 978-989-758-226-4
IS - 2184-4321
AU - Kalliatakis, G.
AU - Ehsan, S.
AU - Fasli, M.
AU - Leonardis, A.
AU - Gall, J.
AU - McDonald-Maier, K.
PY - 2017
SP - 289
EP - 296
DO - 10.5220/0006133902890296
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