activity
20142026
most citedMitigating Advanced Adversarial Attacks with More Advanced Gradient Obfuscation Techniques

14 citations · 61 across the 19 of their papers we have counts for

collaborators

20 papers

cs.DM2026

A note on Finiteness and Boundedness in Cartesian Products of Discrete and Well-Ordered Sets, Application to Transition Systems

Gerard Memmi

In this short note, we prove that any closed interval in a well-ordered and discrete space is finite. The coincidence between finiteness and boundedness can then be established for…

cs.FL2023

Invariants and Home Spaces in Transition Systems and Petri Nets

Gerard Memmi

This lecture note focuses on comparing the notions of invariance and home spaces in Transition Systems and more particularly, in Petri Nets. We also describe how linear algebra rel…

cs.FL2022

A Note on Generating Sets for Semiflows

Gerard Memmi

In this short note, we are interested in discussing characteristics of finite generating sets for , the set of all semiflows with non negative coefficients of a Petri…

cs.CR2020★ 4 cited

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

Yi Zeng, Han Qiu, Gerard Memmi +1

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 wro…

cs.CR2020★ 14 cited

Mitigating Advanced Adversarial Attacks with More Advanced Gradient Obfuscation Techniques

Han Qiu, Yi Zeng, Qinkai Zheng +3

Deep Neural Networks (DNNs) are well-known to be vulnerable to Adversarial Examples (AEs). A large amount of efforts have been spent to launch and heat the arms race between the at…

eess.IV2020

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

Qinkai Zheng, Han Qiu, Gerard Memmi +1

This is the report for the PRIM project in Telecom Paris. This report is about applications based on spatial-frequency transform and deep learning techniques. In this report, there…