39 citations · 119 across the 12 of their papers we have counts for
6 papers · 1 filter
A vision based system for underwater docking
Shuang Liu, Mete Ozay, Takayuki Okatani +3
Autonomous underwater vehicles (AUVs) have been deployed for underwater exploration. However, its potential is confined by its limited on-board battery energy and data storage capa…
HyperNetworks with statistical filtering for defending adversarial examples
Zhun Sun, Mete Ozay, Takayuki Okatani
Deep learning algorithms have been known to be vulnerable to adversarial perturbations in various tasks such as image classification. This problem was addressed by employing severa…
Linear Discriminant Generative Adversarial Networks
Zhun Sun, Mete Ozay, Takayuki Okatani
We develop a novel method for training of GANs for unsupervised and class conditional generation of images, called Linear Discriminant GAN (LD-GAN). The discriminator of an LD-GAN…
Improving Robustness of Feature Representations to Image Deformations using Powered Convolution in CNNs
Zhun Sun, Mete Ozay, Takayuki Okatani
In this work, we address the problem of improvement of robustness of feature representations learned using convolutional neural networks (CNNs) to image deformation. We argue that…
Information Potential Auto-Encoders
Yan Zhang, Mete Ozay, Zhun Sun +1
In this paper, we suggest a framework to make use of mutual information as a regularization criterion to train Auto-Encoders (AEs). In the proposed framework, AEs are regularized b…
Optimization on Product Submanifolds of Convolution Kernels
Mete Ozay, Takayuki Okatani
Recent advances in optimization methods used for training convolutional neural networks (CNNs) with kernels, which are normalized according to particular constraints, have shown re…