b'Lei Ma'

research

∙ 06/14/2022

Learning towards Synchronous Network Memorizability and Generalizability for Continual Segmentation across Multiple Sites

In clinical practice, a segmentation network is often required to contin...

Jingyang Zhang, et al. ∙

research

∙ 06/11/2022

CodeS: A Distribution Shift Benchmark Dataset for Source Code Learning

Over the past few years, deep learning (DL) has been continuously expand...

Qiang Hu, et al. ∙

research

∙ 01/05/2022

Towards Understanding Quality Challenges of the Federated Learning: A First Look from the Lens of Robustness

Federated learning (FL) is a widely adopted distributed learning paradig...

Amin Eslami Abyane, et al. ∙

research

∙ 01/04/2022

A Robust Visual Sampling Model Inspired by Receptive Field

Spike camera mimicking the retina fovea can report per-pixel luminance i...

Liwen Hu, et al. ∙

research

∙ 11/24/2021

Machine Learning Guided Cross-Contract Fuzzing

Smart contract transactions are increasingly interleaved by cross-contra...

Yinxing Xue, et al. ∙

research

∙ 11/08/2021

When Cyber-Physical Systems Meet AI: A Benchmark, an Evaluation, and a Way Forward

Cyber-physical systems (CPS) have been broadly deployed in safety-critic...

Jiayang Song, et al. ∙

research

∙ 10/08/2021

SCFlow: Optical Flow Estimation for Spiking Camera

As a bio-inspired sensor with high temporal resolution, Spiking camera h...

Liwen Hu, et al. ∙

research

∙ 10/07/2021

SkullEngine: A Multi-stage CNN Framework for Collaborative CBCT Image Segmentation and Landmark Detection

We propose a multi-stage coarse-to-fine CNN-based framework, called Skul...

Qin Liu, et al. ∙

research

∙ 09/11/2021

A Self-Supervised Deep Framework for Reference Bony Shape Estimation in Orthognathic Surgical Planning

Virtual orthognathic surgical planning involves simulating surgical corr...

Deqiang Xiao, et al. ∙

research

∙ 03/16/2021

Identifying Bug Patterns in Quantum Programs

Bug patterns are erroneous code idioms or bad coding practices that have...

Pengzhan Zhao, et al. ∙

research

∙ 01/20/2021

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...

Maryam Vahdat Pour, et al. ∙

research

∙ 01/02/2021

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

Complex event processing (CEP) systems continuously evaluate large workl...

Olga Poppe, et al. ∙

research

∙ 10/16/2020

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

Computer vision technology is widely used in biological and medical data...

Ruohua Shi, et al. ∙

research

∙ 09/21/2020

DeepTag: Robust Image Tagging for DeepFake Provenance

In recent years, DeepFake is becoming a common threat to our society, du...

Run Wang, et al. ∙

research

∙ 09/19/2020

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

Single-image deraining is rather challenging due to the unknown rain mod...

Qing Guo, et al. ∙

research

∙ 09/19/2020

FakeRetouch: Evading DeepFakes Detection via the Guidance of Deliberate Noise

The novelty and creativity of DeepFake generation techniques have attrac...

Yihao Huang, et al. ∙

research

∙ 09/19/2020

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...

Liming Zhai, et al. ∙

research

∙ 07/02/2020

Generating Adversarial Examples withControllable Non-transferability

Adversarial attacks against Deep Neural Networks have been widely studie...

Renzhi Wang, et al. ∙

research

∙ 06/13/2020

DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms

As the GAN-based face image and video generation techniques, widely know...

Hua Qi, et al. ∙

research

∙ 06/13/2020

FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction

The recently rapid advances of generative adversarial networks (GANs) in...

Yihao Huang, et al. ∙

research

∙ 05/28/2020

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

With the recent advances in voice synthesis, AI-synthesized fake voices ...

Run Wang, et al. ∙

research

∙ 05/19/2020

An Auto-Context Deformable Registration Network for Infant Brain MRI

Deformable image registration is fundamental to longitudinal and populat...

Dongming Wei, et al. ∙

research

∙ 05/14/2020

Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning

Adversarial attacks against conventional Deep Learning (DL) systems and ...

Jianwen Sun, et al. ∙

research

∙ 04/24/2020

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...

Xiyue Zhang, et al. ∙

research

∙ 02/20/2020

Towards Byzantine-resilient Learning in Decentralized Systems

With the proliferation of IoT and edge computing, decentralized learning...

Shangwei Guo, et al. ∙

research

∙ 02/10/2020

ABBA: Saliency-Regularized Motion-Based Adversarial Blur Attack

Deep neural networks are vulnerable to noise-based adversarial examples,...

Qing Guo, et al. ∙

research

∙ 01/27/2020

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...

Yihao Huang, et al. ∙

research

∙ 12/10/2019

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...

Yinxing Xue, et al. ∙

research

∙ 12/09/2019

Amora: Black-box Adversarial Morphing Attack

Nowadays, digital facial content manipulation has become ubiquitous and ...

Run Wang, et al. ∙

research

∙ 10/19/2019

Spatial-aware Online Adversarial Perturbations Against Visual Object Tracking

Adversarial attacks of deep neural networks have been intensively studie...

Qing Guo, et al. ∙

research

∙ 09/15/2019

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...

Qianyu Guo, et al. ∙

research

∙ 09/14/2019

Oracle-Supported Dynamic Exploit Generation for Smart Contracts

Despite the high stakes involved in smart contracts, they are often deve...

Haijun Wang, et al. ∙

research

∙ 09/13/2019

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

In recent years, we have witnessed the unprecedented success of generati...

Run Wang, et al. ∙

research

∙ 06/19/2019

Machine Learning Testing: Survey, Landscapes and Horizons

This paper provides a comprehensive survey of Machine Learning Testing (...

Jie M. Zhang, et al. ∙

research

∙ 01/10/2019

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-...

Lei Ma, et al. ∙

research

∙ 12/13/2018

DeepCruiser: Automated Guided Testing for Stateful Deep Learning Systems

Deep learning (DL) defines a data-driven programming paradigm that autom...

Xiaoning Du, et al. ∙

research

∙ 11/13/2018

An Orchestrated Empirical Study on Deep Learning Frameworks and Platforms

Deep learning (DL) has recently achieved tremendous success in a variety...

Qianyu Guo, et al. ∙

research

∙ 10/10/2018

Secure Deep Learning Engineering: A Software Quality Assurance Perspective

Over the past decades, deep learning (DL) systems have achieved tremendo...

Lei Ma, et al. ∙

research

∙ 09/07/2018

Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer

Deep neural networks (DNN), while becoming the driving force of many nov...

Alvin Chan, et al. ∙

research

∙ 09/04/2018

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

In company with the data explosion over the past decade, deep neural net...

Xiaofei Xie, et al. ∙

research

∙ 09/04/2018

Coverage-Guided Fuzzing for Deep Neural Networks

In company with the data explosion over the past decade, deep neural net...

Xiaofei Xie, et al. ∙

research

∙ 06/20/2018

Combinatorial Testing for Deep Learning Systems

Deep learning (DL) has achieved remarkable progress over the past decade...

Lei Ma, et al. ∙

research

∙ 06/15/2018

Practical Fault Attack on Deep Neural Networks

As deep learning systems are widely adopted in safety- and security-crit...

Jakub Breier, et al. ∙

research

∙ 05/14/2018

DeepMutation: Mutation Testing of Deep Learning Systems

Deep learning (DL) defines a new data-driven programming paradigm where ...

Lei Ma, et al. ∙

research

∙ 03/20/2018

DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems

Deep learning defines a new data-driven programming paradigm that constr...

Lei Ma, et al. ∙

research

∙ 03/20/2018

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...

Lei Ma, et al. ∙

Lei Ma

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