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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...
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To Share, or not to Share Online Event Trend Aggregation Over Bursty Event Streams
Complex event processing (CEP) systems continuously evaluate large workl...
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Human Perception-based Evaluation Criterion for Ultra-high Resolution Cell Membrane Segmentation
Computer vision technology is widely used in biological and medical data...
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DeepTag: Robust Image Tagging for DeepFake Provenance
In recent years, DeepFake is becoming a common threat to our society, du...
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EfficientDeRain: Learning Pixel-wise Dilation Filtering for High-Efficiency Single-Image Deraining
Single-image deraining is rather challenging due to the unknown rain mod...
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FakeRetouch: Evading DeepFakes Detection via the Guidance of Deliberate Noise
The novelty and creativity of DeepFake generation techniques have attrac...
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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...
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Generating Adversarial Examples withControllable Non-transferability
Adversarial attacks against Deep Neural Networks have been widely studie...
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DeepRhythm: Exposing DeepFakes with Attentional Visual Heartbeat Rhythms
As the GAN-based face image and video generation techniques, widely know...
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FakePolisher: Making DeepFakes More Detection-Evasive by Shallow Reconstruction
The recently rapid advances of generative adversarial networks (GANs) in...
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DeepSonar: Towards Effective and Robust Detection of AI-Synthesized Fake Voices
With the recent advances in voice synthesis, AI-synthesized fake voices ...
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An Auto-Context Deformable Registration Network for Infant Brain MRI
Deformable image registration is fundamental to longitudinal and populat...
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Stealthy and Efficient Adversarial Attacks against Deep Reinforcement Learning
Adversarial attacks against conventional Deep Learning (DL) systems and ...
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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...
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Towards Byzantine-resilient Learning in Decentralized Systems
With the proliferation of IoT and edge computing, decentralized learning...
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ABBA: Saliency-Regularized Motion-Based Adversarial Blur Attack
Deep neural networks are vulnerable to noise-based adversarial examples,...
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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...
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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...
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Amora: Black-box Adversarial Morphing Attack
Nowadays, digital facial content manipulation has become ubiquitous and ...
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Spatial-aware Online Adversarial Perturbations Against Visual Object Tracking
Adversarial attacks of deep neural networks have been intensively studie...
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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...
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Oracle-Supported Dynamic Exploit Generation for Smart Contracts
Despite the high stakes involved in smart contracts, they are often deve...
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FakeSpotter: A Simple Baseline for Spotting AI-Synthesized Fake Faces
In recent years, we have witnessed the unprecedented success of generati...
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Machine Learning Testing: Survey, Landscapes and Horizons
This paper provides a comprehensive survey of Machine Learning Testing (...
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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-...
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DeepCruiser: Automated Guided Testing for Stateful Deep Learning Systems
Deep learning (DL) defines a data-driven programming paradigm that autom...
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An Orchestrated Empirical Study on Deep Learning Frameworks and Platforms
Deep learning (DL) has recently achieved tremendous success in a variety...
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Secure Deep Learning Engineering: A Software Quality Assurance Perspective
Over the past decades, deep learning (DL) systems have achieved tremendo...
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Metamorphic Relation Based Adversarial Attacks on Differentiable Neural Computer
Deep neural networks (DNN), while becoming the driving force of many nov...
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DeepHunter: Hunting Deep Neural Network Defects via Coverage-Guided Fuzzing
In company with the data explosion over the past decade, deep neural net...
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Coverage-Guided Fuzzing for Deep Neural Networks
In company with the data explosion over the past decade, deep neural net...
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Combinatorial Testing for Deep Learning Systems
Deep learning (DL) has achieved remarkable progress over the past decade...
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Practical Fault Attack on Deep Neural Networks
As deep learning systems are widely adopted in safety- and security-crit...
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DeepMutation: Mutation Testing of Deep Learning Systems
Deep learning (DL) defines a new data-driven programming paradigm where ...
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DeepGauge: Multi-Granularity Testing Criteria for Deep Learning Systems
Deep learning defines a new data-driven programming paradigm that constr...
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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...
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