Results 61 to 70 of about 240,849 (326)
Does Physical Adversarial Example Really Matter to Autonomous Driving? Towards System-Level Effect of Adversarial Object Evasion Attack [PDF]
, 2023 Ningfei Wang +4 more
openalex +1 more source
Learnable Diffusion Framework for Mouse V1 Neural Decoding
Advanced Science, EarlyView.We introduce Sensorium‐Viz, a diffusion‐based framework for reconstructing high‐fidelity visual stimuli from mouse primary visual cortex activity. By integrating a novel spatial embedding module with a Diffusion Transformer (DiT) and a synthetic‐response augmentation strategy, our model outperforms state‐of‐the‐art fMRI‐based baselines, enabling robust
Kaiwen Deng +2 more
wiley +1 more source
Advanced Science, EarlyView.This review comprehensively summarizes the atomic defects in TMDs for their applications in sustainable energy storage devices, along with the latest progress in ML methodologies for high‐throughput TEM data analysis, offering insights on how ML‐empowered microscopy facilitates bridging structure–property correlation and inspires knowledge for precise ...
Zheng Luo +6 more
wiley +1 more source
Advanced Science, EarlyView.A probabilistic framework based on random time‐space coding metasurfaces enables control of the spatial distribution of electromagnetic fields temporal statistics. By tailoring the marginal and joint distributions of random codes, electromagnetic fields with desired mean and variance patterns are realized, enabling simultaneous transmission and jamming.
Jia Cheng Li +3 more
wiley +1 more source
Adversarial Examples Identification in an End-to-End System With Image Transformation and Filters
IEEE Access, 2020 Deep learning has been receiving great attention in recent years because of its impressive performance in many tasks. However, the widespread adoption of deep learning also becomes a major security risk for those systems as recent researches have pointed
Dang Duy Thang, Toshihiro Matsui
doaj +1 more source
A risk-security tradeoff in graphical coordination games [PDF]
, 2019 A system relying on the collective behavior of decision-makers can be vulnerable to a variety of adversarial attacks. How well can a system operator protect performance in the face of these risks?
Alizadeh, Mahnoosh +2 more
core +1 more source
Diffusion–Model–Driven Discovery of Ferroelectrics for Photocurrent Applications
Advanced Science, EarlyView.We developed a diffusion model–based generative AI and high‐throughput screening framework that accelerates the discovery of photovoltaic ferroelectrics. By coupling AI driven crystal generation with machine learning and DFT screening, we identified Ca3P2 and LiCdP as new ferroelectric materials exhibiting strong polarization, feasible switching ...
Byung Chul Yeo +3 more
wiley +1 more source
Adversarial Attacks Defense Method Based on Multiple Filtering and Image Rotation
Discrete Dynamics in Nature and Society, 2022 Adversarial examples in an image classification task cause neural networks to predict incorrect class labels with high confidence. Many applications related to image classification, such as self-driving and facial recognition, have been seriously ...
Feng Li, Xuehui Du, Liu Zhang
doaj +1 more source
Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare
Advanced Science, EarlyView.Multimodal biosensing meets multidomain AI. Wearable biosensors capture complementary biochemical and physiological signals, while cross‐device, population‐aware learning aligns noisy, heterogeneous streams. This Review distills key sensing modalities, fusion and calibration strategies, and privacy‐preserving deployment pathways that transform ...
Chenshu Liu +10 more
wiley +1 more source
IDSGAN: Generative Adversarial Networks for Attack Generation against Intrusion Detection
, 2019 As an important tool in security, the intrusion detection system bears the responsibility of the defense to network attacks performed by malicious traffic.
Lin, Zilong, Shi, Yong, Xue, Zhi
core