Results 61 to 70 of about 5,384,791 (287)

Scale-Adaptive Adversarial Patch Attack for Remote Sensing Image Aircraft Detection

Remote Sensing, 2021
With the adversarial attack of convolutional neural networks (CNNs), we are able to generate adversarial patches to make an aircraft undetectable by object detectors instead of covering the aircraft with large camouflage nets. However, aircraft in remote
Mingming Lu, Qi Li, Li Chen, Haifeng Li
doaj   +1 more source

Defense Architecture for Adversarial Examples of Ensemble Model Traffic Based on FeatureDifference Selection [PDF]

Jisuanji kexue
Currently,anomaly traffic detection models that leverage deep learning technologies are increasingly vulnerable to adversarial example attacks.Adversarial training has emerged as a potent defense mechanism against these adversarial attacks.By ...
HE Yuankang, MA Hailong, HU Tao, JIANG Yiming
doaj   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source

Functionalizing Micro‐to‐Mesoscopic Electrode Architectures for Regulating Electron Transfer Behaviors in Electrocatalysis

Advanced Functional Materials, EarlyView.
A systematic review is conducted to assess the influence of electrode architecture across micro‐ to mesoscopic length scales on electron‐transfer pathways in electrocatalysis. We discuss the structure‐activity relationships in electrocatalytic applications, including resource recovery and environmental remediation, and provide cost‐effective, efficient
Manshu Zhao, Jiaojiao Zhang, Shideng Yuan, Xinmeng Yu, Keming Wan, Xiaoguang Duan, Zhining Wang   +6 more
wiley   +1 more source

Role of Structural Disorder on Phonon Transport and Thermal Conductivity in Li6PS5Br

Advanced Functional Materials, EarlyView.
Solid electrolytes are fast ion and slow heat conductors. Although both transport properties are governed by lattice dynamics and atomic structure, their interplay remains poorly understood. Here, we study this interrelation in anion‐ordered and disordered Li6PS5Br.
Lukas Ketter, Ryoma Sasaki, Kyra Strotmann, Wolfgang G. Zeier, Yoshitaka Tateyama   +4 more
wiley   +1 more source

Adversarial Attacks against the Perception System of Autonomous Vehicles

, 2023
The rapid advancement in autonomous driving technology underscores the importance of studying the fragility of perception systems in autonomous vehicles, particularly due to their profound impact on public transportation safety.
Gao, Yuxing (author)
core  

A Statistical Defense Approach for Detecting Adversarial Examples [PDF]

Proceedings of the 2020 International Conference on Pattern Recognition and Intelligent Systems, 2020
Adversarial examples are maliciously modified inputs created to fool deep neural networks (DNN). The discovery of such inputs presents a major issue to the expansion of DNN-based solutions. Many researchers have already contributed to the topic, providing both cutting edge-attack techniques and various defensive strategies.
Alessandro Cennamo, Ido Freeman, Anton Kummert   +2 more
openaire   +4 more sources

Tamper‐Responsive Physical Unclonable Functions via Graphene‐Interlayered Block Copolymer Random Structures

Advanced Materials, EarlyView.
Self‐invalidating multilayer physical unclonable functions (PUFs) integrate fingerprint‐like metal nanopattern bilayers from block copolymer templates with highly reactive reduced graphene oxide (rGO) interlayers. This tamper‐responsive architecture blocks all unauthorized physical and chemical replication attempts while autonomously deactivating ...
Gyu Hui Jo, Dae Hui Park, Jeong‐Ho Jang, Woo Seok Tack, Jin Man Kim, Hak Ki Yu, Hyeong Min Jin, Jang Hwan Kim   +7 more
wiley   +1 more source

From the Discovery of the Giant Magnetocaloric Effect to the Development of High‐Power‐Density Systems

Advanced Materials Technologies, EarlyView.
The article overviews past and current efforts on caloric materials and systems, highlighting the contributions of Ames National Laboratory to the field. Solid‐state caloric heat pumping is an innovative method that can be implemented in a wide range of cooling and heating applications.
Agata Czernuszewicz, Yaroslav Mudryk, Jun Cui, Lucas Griffith, Duane D. Johnson, Julie Slaughter   +5 more
wiley   +1 more source

Detecting Adversarial Examples via Neural Fingerprinting

CoRR, 2018
Deep neural networks are vulnerable to adversarial examples, which dramatically alter model output using small input changes. We propose Neural Fingerprinting, a simple, yet effective method to detect adversarial examples by verifying whether model behavior is consistent with a set of secret fingerprints, inspired by the use of biometric and ...
Dathathri, Sumanth, Zheng, Stephan, Yin, Tianwei, Murray, Richard M., Yue, Yisong   +4 more
openaire   +2 more sources