2 citations · 4 across the 3 of their papers we have counts for
4 papers
Camera Bias in a Fine Grained Classification Task
Philip T. Jackson, Stephen Bonner, Ning Jia +3
We show that correlations between the camera used to acquire an image and the class label of that image can be exploited by convolutional neural networks (CNN), resulting in a mode…
A study of the effect of the illumination model on the generation of synthetic training datasets
Xin Zhang, Ning Jia, Ioannis Ivrissimtzis
The use of computer generated images to train Deep Neural Networks is a viable alternative to real images when the latter are scarce or expensive. In this paper, we study how the i…
Watermark retrieval from 3D printed objects via synthetic data training
Xin Zhang, Ning Jia, Ioannis Ivrissimtzis
We present a deep neural network based method for the retrieval of watermarks from images of 3D printed objects. To deal with the variability of all possible 3D printing and image…
A Baseline for Multi-Label Image Classification Using An Ensemble of Deep Convolutional Neural Networks
Qian Wang, Ning Jia, Toby P. Breckon
Recent studies on multi-label image classification have focused on designing more complex architectures of deep neural networks such as the use of attention mechanisms and region p…