Results 161 to 170 of about 3,240,231 (313)
Robustness Against Adversarial Attacks via Learning Confined Adversarial Polytopes [PDF]
Deep neural networks (DNNs) could be deceived by generating human-imperceptible perturbations of clean samples. Therefore, enhancing the robustness of DNNs against adversarial attacks is a crucial task.
Ye, Linfeng, Hamidi, Shayan Mohajer
core +1 more source
RobustCheck: A Python package for black-box robustness assessment of image classifiers
SoftwareXThe robustness of computer vision models against adversarial attacks is a critical matter in machine learning that is often overlooked by researchers and developers.
Andrei Ilie, Alin Stefanescu
doaj +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
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 +2 more
wiley +1 more source
Financial Development in Adversarial and Inquisitorial Legal Systems [PDF]
This paper analyzes how the adversarial and inquisitorial evidence collection procedures affect financial development. In investigating the true returns of insolvent entrepreneurs, the adversarial procedure relies on lawyers whereas the inquisitorial ...
Massenot Baptiste
core
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 +4 more
wiley +1 more source
Adversarial Robustness of Graph Transformers
Trans. Mach. Learn. Res.TMLR 2025 (J2C-Certification: Presented @ ICLR 2026). A preliminary version appeared at the Differentiable Almost Everything Workshop at ICML 2024.
Philipp Foth +4 more
openaire +3 more sources
Predicting Performance of Hall Effect Ion Source Using Machine Learning
Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.This study introduces HallNN, a machine learning tool for predicting Hall effect ion source performance using a neural network ensemble trained on data generated from numerical simulations. HallNN provides faster and more accurate predictions than numerical methods and traditional scaling laws, making it valuable for designing and optimizing Hall ...
Jaehong Park +8 more
wiley +1 more source
Adversarial Robustness of Self-Supervised Learning Features
IEEE Open Journal of Signal ProcessingAs deep learning models have proliferated, concerns about their reliability and security have also increased. One significant challenge is understanding adversarial perturbations, which can alter a model's predictions despite being very small in ...
Nicholas Mehlman, Shri Narayanan
doaj +1 more source
Advanced Intelligent Systems, EarlyView.Neuro‐evolution can boost machine‐learning optimization of chiral metasurfaces. By integrating the NEAT algorithm into a deep‐learning framework, we enable the efficient design of visible‐spectrum chiroptical responses. NEAT autonomously evolves neural‐network architectures and weights, reducing manual tuning.
Davide Filippozzi, Arash Rahimi‐Iman
wiley +1 more source