Results 121 to 130 of about 22,784,147 (354)

RAILS: A Robust Adversarial Immune-inspired Learning System [PDF]

, 2020
Ren Wang, Tianqi Chen, Stephen Lindsly, Alnawaz Rehemtulla, Alfred O. Hero, Indika Rajapakse   +5 more
openalex   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

A Holistic Review of Machine Learning Adversarial Attacks in IoT Networks

Future Internet
With the rapid advancements and notable achievements across various application domains, Machine Learning (ML) has become a vital element within the Internet of Things (IoT) ecosystem.
Hassan Khazane, Mohammed Ridouani, Fatima Salahdine, N. Kaabouch   +3 more
semanticscholar   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

Adversarial Attacks on GMM i-vector based Speaker Verification Systems [PDF]

, 2019
Xu Li, Jinghua Zhong, Xixin Wu, Jianwei Yu, Xunying Liu, Helen Meng   +5 more
openalex   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

A Review on Recent Trends of Bioinspired Soft Robotics: Actuators, Control Methods, Materials Selection, Sensors, Challenges, and Future Prospects

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
This article reviews the current state of bioinspired soft robotics. The article discusses soft actuators, soft sensors, materials selection, and control methods used in bioinspired soft robotics. It also highlights the challenges and future prospects of this field.
Abhirup Sarker, Tamzid Ul Islam, Md. Robiul Islam   +2 more
wiley   +1 more source

Large Language Model‐Based Chatbots in Higher Education

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of large language models (LLMs) in higher education can facilitate personalized learning experiences, advance asynchronized learning, and support instructors, students, and researchers across diverse fields. The development of regulations and guidelines that address ethical and legal issues is essential to ensure safe and responsible adaptation
Defne Yigci, Merve Eryilmaz, Ail K. Yetisen, Savas Tasoglu, Aydogan Ozcan   +4 more
wiley   +1 more source

Adversarial detection based on feature invariant in license plate recognition systems

网络与信息安全学报
Deep neural networks have become an integral part of people's daily lives. However, researchers observed that these networks were susceptible to threats from adversarial samples, leading to abnormal behaviors such as misclassification by the network ...
ZHU Xiaoyu, TANG Peng, ZHANG Haochen, QIU Weidong, HUANG Zheng   +4 more
doaj  

Adversarial Attacks to Classification Systems

, 2022
Amostras adversariais são inputs corrompidos com perturbações pouco visíveis, que são classificadas incorretamente por um determinado modelo alvo. Adversários criam amostras adversariais a partir de vários métodos que dependem da informação disponível sobre o sistema alvo. Num cenário white-box, os adversários tem acesso completo ao modelo enquanto que,
openaire   +1 more source