Results 31 to 40 of about 6,980 (145)
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park +19 more
wiley +1 more source
As with classification models, object detection models are vulnerable to adversarial attacks. In particular, adversarial attacks on key components of object detection models such as Region Proposal Network (RPN) and Non-Maximum Suppression (NMS ...
Gwang-Nam Kim +4 more
doaj +1 more source
A Distributed Biased Boundary Attack Method in Black-Box Attack
The adversarial samples threaten the effectiveness of machine learning (ML) models and algorithms in many applications. In particular, black-box attack methods are quite close to actual scenarios.
Fengtao Xiang +3 more
doaj +1 more source
Large Language Model‐Based Chatbots in Higher Education
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 +4 more
wiley +1 more source
Deep neural networks (DNNs) have achieved great success in various applications due to their strong expressive power. However, recent studies have shown that DNNs are vulnerable to adversarial examples, and these manipulated instances can mislead DNN ...
Jianyi Liu +4 more
doaj +1 more source
Artificial Intelligence for Advanced Functional Materials: Progress and Emerging Frontiers
Artificial intelligence is transforming the discovery of functional materials by linking synthesis, characterization, simulation, and design in unified workflows. Advances in machine learning, autonomous experimentation, and foundation models are accelerating innovation across energy, electronics, and biomedicine, while revealing new frontiers for ...
Cristiano Malica +38 more
wiley +1 more source
A smartphone‐embedded fabric‐strip sensing interface captures side‐pressure sequences and grip‐position patterns for behavioral authentication. Probability‐based soft stacking integrates class‐wise predictive probabilities from multiple learners to improve verification‐style discrimination, supporting a sensor‐integrated mobile‐security framework that ...
Wonki Hong
wiley +1 more source
Secure Fusion‐X harmonizes unstructured NVD descriptions with structured CVSS/CWE/CPE metadata via decision‐level fusion, overcoming the fragility of traditional unimodal models. Automated assessment of software vulnerability exploitability is essential for intelligent cyber defense, yet its effectiveness is often hindered by unstable, delayed, or ...
Mona Dolati +3 more
wiley +1 more source
Multi-Level Chinese Adversarial Example Generation Method Based on Glyph and Semantic [PDF]
Deep neural network language models are vulnerable to adversarial example attacks during application. To address this issue, adversarial examples are typically generated by adding minor perturbations to the original samples to mislead the model into ...
SUN Yu, WANG Hongjie, DU Yanhui, LIU Nan
doaj +1 more source
Bridging the translational gap in clinical nanomedicine: From rational design to clinical reality
Nanotechnology offers a multi‐faceted approach to modern healthcare, encompassing high‐sensitivity diagnostic imaging, innovative vaccine delivery, and targeted therapeutics. This review explores how these nanomedicine applications address critical challenges in cancer recurrence and the treatment of neurologic and respiratory diseases to combat rising
Ahmed H. Ghonaim +9 more
wiley +1 more source

