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20172019
most citedHyperNetworks with statistical filtering for defending adversarial examples

13 citations · 25 across the 6 of their papers we have counts for

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5 papers · 1 filter

cs.CV20192 cited

Improving Head Pose Estimation with a Combined Loss and Bounding Box Margin Adjustment

Mingzhen Shao, Zhun Sun, Mete Ozay +1

We address a problem of estimating pose of a person's head from its RGB image. The employment of CNNs for the problem has contributed to significant improvement in accuracy in rece…

cs.CV2018

Revisiting Single Image Depth Estimation: Toward Higher Resolution Maps with Accurate Object Boundaries

Junjie Hu, Mete Ozay, Yan Zhang +1

This paper considers the problem of single image depth estimation. The employment of convolutional neural networks (CNNs) has recently brought about significant advancements in the…

cs.CV20172 cited

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…

cs.CV201713 cited

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…

cs.CV20171 cited

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…