Search Results for author: Han Qiu

Found 13 papers, 4 papers with code

A Novel Verifiable Fingerprinting Scheme for Generative Adversarial Networks

no code implementations19 Jun 2021 Guanlin Li, Guowen Xu, Han Qiu, Shangwei Guo, Run Wang, Jiwei Li, Tianwei Zhang

Our scheme constructs a composite deep learning model from the target GAN and a classifier.

DeepSweep: An Evaluation Framework for Mitigating DNN Backdoor Attacks using Data Augmentation

no code implementations13 Dec 2020 Han Qiu, Yi Zeng, Shangwei Guo, Tianwei Zhang, Meikang Qiu, Bhavani Thuraisingham

In this paper, we investigate the effectiveness of data augmentation techniques in mitigating backdoor attacks and enhancing DL models' robustness.

Data Augmentation

FenceBox: A Platform for Defeating Adversarial Examples with Data Augmentation Techniques

1 code implementation3 Dec 2020 Han Qiu, Yi Zeng, Tianwei Zhang, Yong Jiang, Meikang Qiu

With more and more advanced adversarial attack methods have been developed, a quantity of corresponding defense solutions were designed to enhance the robustness of DNN models.

Adversarial Attack Data Augmentation

Privacy-preserving Collaborative Learning with Automatic Transformation Search

1 code implementation CVPR 2021 Wei Gao, Shangwei Guo, Tianwei Zhang, Han Qiu, Yonggang Wen, Yang Liu

Comprehensive evaluations demonstrate that the policies discovered by our method can defeat existing reconstruction attacks in collaborative learning, with high efficiency and negligible impact on the model performance.

Data Augmentation

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

no code implementations30 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

BorderDet: Border Feature for Dense Object Detection

1 code implementation ECCV 2020 Han Qiu, Yuchen Ma, Zeming Li, Songtao Liu, Jian Sun

In this paper, We propose a simple and efficient operator called Border-Align to extract "border features" from the extreme point of the border to enhance the point feature.

Dense Object Detection

Mitigating Advanced Adversarial Attacks with More Advanced Gradient Obfuscation Techniques

1 code implementation27 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.

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

no code implementations20 Mar 2020 Qinkai Zheng, Han Qiu, Gerard Memmi, Isabelle Bloch

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


Learning to Augment Expressions for Few-shot Fine-grained Facial Expression Recognition

no code implementations17 Jan 2020 Wenxuan Wang, Yanwei Fu, Qiang Sun, Tao Chen, Chenjie Cao, Ziqi Zheng, Guoqiang Xu, Han Qiu, Yu-Gang Jiang, xiangyang xue

Considering the phenomenon of uneven data distribution and lack of samples is common in real-world scenarios, we further evaluate several tasks of few-shot expression learning by virtue of our F2ED, which are to recognize the facial expressions given only few training instances.

Facial Expression Recognition

TEST: an End-to-End Network Traffic Examination and Identification Framework Based on Spatio-Temporal Features Extraction

no code implementations26 Aug 2019 Yi Zeng, Zihao Qi, Wen-Cheng Chen, Yanzhe Huang, Xingxin Zheng, Han Qiu

With more encrypted network traffic gets involved in the Internet, how to effectively identify network traffic has become a top priority in the field.

Intrusion Detection Traffic Classification

Learning Correlation Space for Time Series

no code implementations10 Feb 2018 Han Qiu, Hoang Thanh Lam, Francesco Fusco, Mathieu Sinn

We propose an approximation algorithm for efficient correlation search in time series data.

Time Series

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