Results 161 to 170 of about 124,232 (320)
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
Semantically Decomposing the Latent Spaces of Generative Adversarial Networks
, 2017 Chris Donahue +3 more
openalex +2 more sources
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
How Well Can Generative Adversarial Networks Learn Densities: A Nonparametric View
, 2017 Tengyuan Liang
openalex +2 more sources
Generalization of Deep Neural Networks for Chest Pathology Classification in X-Rays Using Generative Adversarial Networks [PDF]
, 2018 Hojjat Salehinejad +4 more
openalex +1 more source
Advancements in Machine Learning for Microrobotics in Biomedicine
Advanced Intelligent Systems, EarlyView.Microrobotics is an innovative technology with great potential for noninvasive medical interventions. However, controlling and imaging microrobots pose significant challenges in complex environments and in living organisms. This review explores how machine learning algorithms can address these issues, offering solutions for adaptive motion control and ...
Amar Salehi +6 more
wiley +1 more source
Stochastic Reconstruction of an Oolitic Limestone by Generative Adversarial Networks [PDF]
, 2018 Lukas Mosser +2 more
openalex +1 more source
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
Bidirectional Conditional Generative Adversarial Networks
, 2017 Ayush Jaiswal +3 more
openalex +2 more sources
Advanced Intelligent Systems, EarlyView.Autofluorescence imaging with virtual histological staining streamlines postoperative histopathology. Using a deep ultraviolet light‐emitting diode (LED)‐based imaging system and a weakly supervised deep learning model, virtual hematoxylin and eosin (H&E)‐stained images are generated from the autofluorescence of prostate tissue. Pathologist evaluations
Mingxuan Si +9 more
wiley +1 more source