Investigating Image Applications Based on Spatial-Frequency Transform and Deep Learning Techniques

no code implementations • 20 Mar 2020 • Qinkai Zheng, Han Qiu, Gerard Memmi, Isabelle Bloch

This report is about applications based on spatial-frequency transform and deep learning techniques.

Denoising

Mitigating Advanced Adversarial Attacks with More Advanced Gradient Obfuscation Techniques

1 code implementation • 27 May 2020 • Han Qiu, Yi Zeng, Qinkai Zheng, Tianwei Zhang, Meikang Qiu, Gerard Memmi

Extensive evaluations indicate that our solutions can effectively mitigate all existing standard and advanced attack techniques, and beat 11 state-of-the-art defense solutions published in top-tier conferences over the past 2 years.

A Data Augmentation-based Defense Method Against Adversarial Attacks in Neural Networks

no code implementations • 30 Jul 2020 • Yi Zeng, Han Qiu, Gerard Memmi, Meikang Qiu

Deep Neural Networks (DNNs) in Computer Vision (CV) are well-known to be vulnerable to Adversarial Examples (AEs), namely imperceptible perturbations added maliciously to cause wrong classification results.

Data Augmentation