b'Lei Ma'

A Search-Based Testing Framework for Deep Neural Networks of Source Code Embedding

Over the past few years, deep neural networks (DNNs) have been continuou...
01/20/2021 ∙ by Maryam Vahdat Pour, et al. ∙ 0 ∙ share

read it
To Share, or not to Share Online Event Trend Aggregation Over Bursty Event Streams

Complex event processing (CEP) systems continuously evaluate large workl...
01/02/2021 ∙ by Olga Poppe, et al. ∙ 0 ∙ share

read it
Human Perception-based Evaluation Criterion for Ultra-high Resolution Cell Membrane Segmentation

Computer vision technology is widely used in biological and medical data...
10/16/2020 ∙ by Ruohua Shi, et al. ∙ 11 ∙ share

read it
DeepTag: Robust Image Tagging for DeepFake Provenance

In recent years, DeepFake is becoming a common threat to our society, du...
09/21/2020 ∙ by Run Wang, et al. ∙ 0 ∙ share

read it
EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining

Single-image deraining is rather challenging due to the unknown rain mod...
09/19/2020 ∙ by Qing Guo, et al. ∙ 11 ∙ share

read it
FakeRetouch: Evading DeepFakes Detection via the Guidance of Deliberate Noise

The novelty and creativity of DeepFake generation techniques have attrac...
09/19/2020 ∙ by Yihao Huang, et al. ∙ 37 ∙ share

read it
It's Raining Cats or Dogs? Adversarial Rain Attack on DNN Perception

Rain is a common phenomenon in nature and an essential factor for many d...
09/19/2020 ∙ by Liming Zhai, et al. ∙ 1 ∙ share

read it
Generating Adversarial Examples withControllable Non-transferability

Adversarial attacks against Deep Neural Networks have been widely studie...
07/02/2020 ∙ by Renzhi Wang, et al. ∙ 0 ∙ share

read it
DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms

As the GAN-based face image and video generation techniques, widely know...
06/13/2020 ∙ by Hua Qi, et al. ∙ 12 ∙ share

read it
FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction

The recently rapid advances of generative adversarial networks (GANs) in...
06/13/2020 ∙ by Yihao Huang, et al. ∙ 5 ∙ share

read it
DeepSonar: Towards Effective and Robust Detection of AI-Synthesized Fake Voices

With the recent advances in voice synthesis, AI-synthesized fake voices ...
05/28/2020 ∙ by Run Wang, et al. ∙ 0 ∙ share

read it
An Auto-Context Deformable Registration Network for Infant Brain MRI

Deformable image registration is fundamental to longitudinal and populat...
05/19/2020 ∙ by Dongming Wei, et al. ∙ 0 ∙ share

read it
Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

Adversarial attacks against conventional Deep Learning (DL) systems and ...
05/14/2020 ∙ by Jianwen Sun, et al. ∙ 2 ∙ share

read it
Towards Characterizing Adversarial Defects of Deep Learning Software from the Lens of Uncertainty

Over the past decade, deep learning (DL) has been successfully applied t...
04/24/2020 ∙ by Xiyue Zhang, et al. ∙ 0 ∙ share

read it
Towards Byzantine-resilient Learning in Decentralized Systems

With the proliferation of IoT and edge computing, decentralized learning...
02/20/2020 ∙ by Shangwei Guo, et al. ∙ 0 ∙ share

read it
ABBA: Saliency-Regularized Motion-Based Adversarial Blur Attack

Deep neural networks are vulnerable to noise-based adversarial examples,...
02/10/2020 ∙ by Qing Guo, et al. ∙ 6 ∙ share

read it
FakeLocator: Robust Localization of GAN-Based Face Manipulations via Semantic Segmentation Networks with Bells and Whistles

Nowadays, full face synthesis and partial face manipulation by virtue of...
01/27/2020 ∙ by Yihao Huang, et al. ∙ 0 ∙ share

read it
Doublade: Unknown Vulnerability Detection in Smart Contracts Via Abstract Signature Matching and Refined Detection Rules

With the prosperity of smart contracts and the blockchain technology, va...
12/10/2019 ∙ by Yinxing Xue, et al. ∙ 0 ∙ share

read it
Amora: Black-box Adversarial Morphing Attack

Nowadays, digital facial content manipulation has become ubiquitous and ...
12/09/2019 ∙ by Run Wang, et al. ∙ 30 ∙ share

read it
Spatial-aware Online Adversarial Perturbations Against Visual Object Tracking

Adversarial attacks of deep neural networks have been intensively studie...
10/19/2019 ∙ by Qing Guo, et al. ∙ 0 ∙ share

read it
An Empirical Study towards Characterizing Deep Learning Development and Deployment across Different Frameworks and Platforms

Deep Learning (DL) has recently achieved tremendous success. A variety o...
09/15/2019 ∙ by Qianyu Guo, et al. ∙ 0 ∙ share

read it
Oracle-Supported Dynamic Exploit Generation for Smart Contracts

Despite the high stakes involved in smart contracts, they are often deve...
09/14/2019 ∙ by Haijun Wang, et al. ∙ 0 ∙ share

read it
FakeSpotter: A Simple Baseline for Spotting AI-Synthesized Fake Faces

In recent years, we have witnessed the unprecedented success of generati...
09/13/2019 ∙ by Run Wang, et al. ∙ 31 ∙ share

read it
Machine Learning Testing: Survey, Landscapes and Horizons

This paper provides a comprehensive survey of Machine Learning Testing (...
06/19/2019 ∙ by Jie M. Zhang, et al. ∙ 0 ∙ share

read it
Hierarchy Neighborhood Discriminative Hashing for An Unified View of Single-Label and Multi-Label Image retrieval

Recently, deep supervised hashing methods have become popular for large-...
01/10/2019 ∙ by Lei Ma, et al. ∙ 0 ∙ share

read it
DeepCruiser: Automated Guided Testing for Stateful Deep Learning Systems

Deep learning (DL) defines a data-driven programming paradigm that autom...
12/13/2018 ∙ by Xiaoning Du, et al. ∙ 0 ∙ share

read it
An Orchestrated Empirical Study on Deep Learning Frameworks and Platforms

Deep learning (DL) has recently achieved tremendous success in a variety...
11/13/2018 ∙ by Qianyu Guo, et al. ∙ 2 ∙ share

read it
Secure Deep Learning Engineering: A Software Quality Assurance Perspective

Over the past decades, deep learning (DL) systems have achieved tremendo...
10/10/2018 ∙ by Lei Ma, et al. ∙ 0 ∙ share

read it
Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer

Deep neural networks (DNN), while becoming the driving force of many nov...
09/07/2018 ∙ by Alvin Chan, et al. ∙ 0 ∙ share

read it
DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing

In company with the data explosion over the past decade, deep neural net...
09/04/2018 ∙ by Xiaofei Xie, et al. ∙ 0 ∙ share

read it
Coverage-Guided Fuzzing for Deep Neural Networks

In company with the data explosion over the past decade, deep neural net...
09/04/2018 ∙ by Xiaofei Xie, et al. ∙ 0 ∙ share

read it
Combinatorial Testing for Deep Learning Systems

Deep learning (DL) has achieved remarkable progress over the past decade...
06/20/2018 ∙ by Lei Ma, et al. ∙ 0 ∙ share

read it
Practical Fault Attack on Deep Neural Networks

As deep learning systems are widely adopted in safety- and security-crit...
06/15/2018 ∙ by Jakub Breier, et al. ∙ 0 ∙ share

read it
DeepMutation: Mutation Testing of Deep Learning Systems

Deep learning (DL) defines a new data-driven programming paradigm where ...
05/14/2018 ∙ by Lei Ma, et al. ∙ 0 ∙ share

read it
DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems

Deep learning defines a new data-driven programming paradigm that constr...
03/20/2018 ∙ by Lei Ma, et al. ∙ 0 ∙ share

read it
DeepGauge: Comprehensive and Multi-Granularity Testing Criteria for Gauging the Robustness of Deep Learning Systems

Deep learning defines a new data-driven programming paradigm that constr...
03/20/2018 ∙ by Lei Ma, et al. ∙ 0 ∙ share

read it

Lei Ma

Featured Co-authors