Zobrazeno 1 - 3
of 3
pro vyhledávání: '"Easom, Philip"'
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
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