Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Dinakaran, Ranjith"'
Publikováno v:
FLINS 2020
In-vehicle human object identification plays an important role in vision-based automated vehicle driving systems while objects such as pedestrians and vehicles on roads or streets are the primary targets to protect from driverless vehicles. A challen
Externí odkaz:
http://arxiv.org/abs/2004.12700
Autor:
Dinakaran, Ranjith, Easom, Philip, Zhang, Li, Bouridane, Ahmed, Jiang, Richard, Edirisinghe, Eran
Publikováno v:
The 2019 International Joint Conference on Neural Networks (IJCNN)
In this work, we examine the feasibility of applying Deep Convolutional Generative Adversarial Networks (DCGANs) with Single Shot Detector (SSD) as data-processing technique to handle with the challenge of pedestrian detection in the wild. Specifical
Externí odkaz:
http://arxiv.org/abs/1905.12759
Autor:
Dinakaran, Ranjith K, Easom, Philip, Bouridane, Ahmed, Zhang, Li, Jiang, Richard, Mehboob, Fozia, Rauf, Abdul
Generative adversarial networks (GANs) have been promising for many computer vision problems due to their powerful capabilities to enhance the data for training and test. In this paper, we leveraged GANs and proposed a new architecture with a cascade
Externí odkaz:
http://arxiv.org/abs/1812.00876
Autor:
Dinakaran, Ranjith1 (AUTHOR) ranjith.dinakaran@northumbria.ac.uk, Zhang, Li2 (AUTHOR) li.zhang@rhul.ac.uk, Li, Chang-Tsun3 (AUTHOR) changtsun.li@deakin.edu.au, Bouridane, Ahmed4 (AUTHOR) abouridane@sharjah.ac.ae, Jiang, Richard5 (AUTHOR) r.jiang2@lancaster.ac.uk
Publikováno v:
Remote Sensing. Aug2022, Vol. 14 Issue 15, p3680-3680. 17p.
Publikováno v:
ISC 2018-International Conference on Information Society and Smart Cities
Face detection from unconstrained “in the wild” images such as those obtained from CCTV and other image capture devices used within urban environments can provide a rich source of information about citizens within the urban environments benefitin
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=core_ac_uk__::cea2f78c738dd8e242c8cd51cf23efc6
Publikováno v:
ACM International Conference Proceeding Series; 10/17/2019, p1-8, 8p