Results 71 to 80 of about 22,784,147 (354)
Adversarial Attacks Defense Method Based on Multiple Filtering and Image Rotation
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
Adversarial Swarms as Dynamical Systems
An Adversarial Swarm model consists of two swarms that are interacting with each other in a competing manner. In the present study, an agent-based Adversarial swarm model is developed comprising of two competing swarms, the Attackers and the Defenders, respectively.
Gupta, Soham, Baker, John
openaire +2 more sources
ZNRD2 Mediated Nucleoprotein Aggregation Impairs Respiratory Syncytial Virus Replication
During RSV infection, nucleoprotein (N) forms RNA‐bound oligomers. The host protein ZNRD2 binds to these oligomers, promoting their transition into insoluble aggregates. These aggregates simultaneously sequester functional N to restrict viral production and disrupt chaperonin assembly quality control by interfering with ZNRD2's role as an adaptor ...
Haiwu Zhou +8 more
wiley +1 more source
This study presents a novel microscopic imaging system capable of rapid, section‐free scanning of irregular tissue surfaces, delivering high sensitivity for detecting cancer cell clusters during intraoperative tumor margin assessment. Abstract Rapid and accurate intraoperative examination of tumor margins is crucial for precise surgical treatment, yet ...
Zhicheng Shao +17 more
wiley +1 more source
Unpaired Learning‐Enabled Nanotube Identification from AFM Images
Identifying nanotubes on rough substrates is notoriously challenging for conventional image analysis. This work presents an unpaired deep learning approach that automatically extracts nanotube networks from atomic force microscopy images, even on complex polymeric surfaces used in roll‐to‐roll printing.
Soyoung Na +10 more
wiley +1 more source
We present Diffusion‐MRI‐based Estimation of Cortical Architecture via Machine Learning (DECAM), a deep‐learning framework for estimating primate brain cortical architecture optimized with best response constraint and cortical label vectors. Trained using macaque brain high‐resolution multi‐shell dMRI and histology data, DECAM generates high‐fidelity ...
Tianjia Zhu +7 more
wiley +1 more source
Adversarial Samples on Android Malware Detection Systems for IoT Systems [PDF]
Many IoT (Internet of Things) systems run Android systems or Android-like systems. With the continuous development of machine learning algorithms, the learning-based Android malware detection system for IoT devices has gradually increased. However, these learning-based detection models are often vulnerable to adversarial samples.
Xiaolei Liu +5 more
openaire +7 more sources
A neuromorphic computing platform using spin‐orbit torque‐controlled magnetic textures is reported. The device implements bio‐inspired synaptic functions and achieves high performance in both pattern recognition (>93%) and combinatorial optimization (>95%), enabling unified processing of cognitive and optimization tasks.
Yifan Zhang +13 more
wiley +1 more source
A survey of practical adversarial example attacks
Adversarial examples revealed the weakness of machine learning techniques in terms of robustness, which moreover inspired adversaries to make use of the weakness to attack systems employing machine learning.
Lu Sun, Mingtian Tan, Zhe Zhou
doaj +1 more source
scPER presents an adversarial‐autoencoder framework that deconvolves bulk total RNA‐seq to quantify tumor‐microenvironment cell types and uncover phenotype‐linked subclusters. Across diverse benchmarks, scPER improves accuracy over existing tools.
Bingrui Li, Xiaobo Zhou, Raghu Kalluri
wiley +1 more source

