Results 151 to 160 of about 39,370 (305)

Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy

Advanced Intelligent Discovery, EarlyView.
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang, Andrew Bai, Alexandra Bermudez, Yunqi Hong, Zoe Latham, Iris Sloan, Michael Liu, Vishrut Goyal, Cho‐Jui Hsieh, Neil Y. C. Lin   +9 more
wiley   +1 more source

Hamiltonian quantum generative adversarial networks

Physical Review Research
We propose Hamiltonian quantum generative adversarial networks (HQuGANs) to learn to generate unknown input quantum states using two competing quantum optimal controls. The game-theoretic framework of the algorithm is inspired by the success of classical
Leeseok Kim, Seth Lloyd, Milad Marvian
doaj   +1 more source

Transformative skeletal motion analysis: optimization of exercise training and injury prevention through graph neural networks

Frontiers in Neuroscience
IntroductionExercise is pivotal for maintaining physical health in contemporary society. However, improper postures and movements during exercise can result in sports injuries, underscoring the significance of skeletal motion analysis. This research aims
Jiaju Zhu, Zijun Ye, Meixue Ren, Guodong Ma, Guodong Ma   +4 more
doaj   +1 more source

Wasserstein Generative Adversarial Networks for Realistic Traffic Sign Image Generation

, 2021
Wasserstein Generative Adversarial Networks for Realistic Traffic Sign Image ...
Yan-Ting Liu (17719110), Rung-Ching Chen (12272613), Christine Dewi (18586621)   +2 more
core  

Accelerating Discovery of Organic Molecular Crystals via Materials Informatics and Autonomous Experiments

Advanced Intelligent Discovery, EarlyView.
Materials informatics and autonomous experimentation are transforming the discovery of organic molecular crystals. This review presents an integrated molecule–crystal–function–optimization workflow combining machine learning, crystal structure prediction, and Bayesian optimization with robotic platforms.
Takuya Taniguchi, Kazuki Ishizaki, Ryo Fukasawa   +2 more
wiley   +1 more source

Advancing student outcome predictions through generative adversarial networks

Computers and Education: Artificial Intelligence
Predicting student outcomes is essential in educational analytics for creating personalised learning experiences. The effectiveness of these predictive models relies on having access to sufficient and accurate data. However, privacy concerns and the lack
Helia Farhood, Ibrahim Joudah, Amin Beheshti, Samuel Muller   +3 more
doaj   +1 more source

Semi-supervised generative adversarial networks for improved colorectal polyp classification using histopathological images

Early and accurate detection of dysplasia in colorectal polyps can improve prognosis and increase survival chances. Recently, automated learning-based approaches using histopathological images have been adopted for improved classification of polyps.
Sharma, Vanshali, Allam, Allam Jaya, Patro, Kiran Kumar, Iwahori, Yuji, Alamro, Hayam, Bhuyan, M.K., Samee, Nagwan Abdel, Acharya, U. Rajendra, Tadeusiewicz, Ryszard, Pławiak, Paweł, Sasmal, Pradipta   +10 more
core   +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

Image Denoising Using Quantum Deep Convolutional Generative Adversarial Network for Medical Images

International Journal of Computational Intelligence Systems
A significant role is played by medical images in diagnosing diseases and planning the course of treatment. Noise can potentially degrade the quality of images which can lead to misdiagnosis.
Priyanka Nandal, Sudesh Pahal, Govind Murari Upadhyay   +2 more
doaj   +1 more source

Semi-supervised community detection method based on generative adversarial networks

Journal of King Saud University: Computer and Information Sciences
Community detection in complex networks often suffers from insufficient data and limited utilization of prior knowledge. In this paper we propose “Semi-supervised Generative Adversarial Network” (GANSE), a novel algorithm that integrates Generative ...
Xiaoyang Liu, Mengyao Zhang, Yanfei Liu, Chao Liu, Chaorong Li, Wei Wang, Xiaoqin Zhang, Asgarali Bouyer   +7 more
doaj   +1 more source