Results 211 to 220 of about 60,338 (274)

Generative Models for Medical Image Creation and Translation: A Scoping Review. [PDF]

Sensors (Basel)
Pang H, Zhang T, Wu Y, Chen S, Qian W, Yao Y, Ye C, Monkam P, Qi S.   +8 more
europepmc   +1 more source

What to Make and How to Make It: Combining Machine Learning and Statistical Learning to Design New Materials

Advanced Intelligent Discovery, Volume 2, Issue 2, April 2026.
Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley   +1 more source

Attention-Enhanced GAN for Astronomical Image Restoration Under Atmospheric Turbulence and Optical Aberrations. [PDF]

Sensors (Basel)
Peng C, Li J, Bao J, Luo L.
europepmc   +1 more source

Inverse Design of Alloys via Generative Algorithms: Optimization and Diffusion within Learned Latent Space

Advanced Intelligent Discovery, Volume 2, Issue 2, April 2026.
This work presents a novel generative artificial intelligence (AI) framework for inverse alloy design through operations (optimization and diffusion) within learned compact latent space from variational autoencoder (VAE). The proposed work addresses challenges of limited data, nonuniqueness solutions, and high‐dimensional spaces.
Mohammad Abu‐Mualla, Ellis Crabtree, Fredrick Michael, Yayue Pan, Jida Huang   +4 more
wiley   +1 more source

Gross-tumor-volume segment-anything model for medical 2D images integrating gross tumor volume-minimal feature integration technology for lung cancer segmentation. [PDF]

Quant Imaging Med Surg
Yi C, Li Y, Cao S, Xiong Q, Jiang S, Zhang H.   +5 more
europepmc   +1 more source

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, Volume 8, Issue 4, April 2026.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

Conditional noise generative adversarial networks with Siamese neural network for longer time series forecasting. [PDF]

Sci Rep
Mao H, Feng X.
europepmc   +1 more source

Feature Disentangling and Combination Implemented by Spin–Orbit Torque Magnetic Tunnel Junctions

Advanced Intelligent Systems, Volume 8, Issue 4, April 2026.
Spin–orbit torque magnetic tunnel junctions (SOT‐MTJs) enable efficient feature disentangling and integration in image data. A proposed algorithm leverages SOT‐MTJs as true random number generators to disentangle and recombine features in real time, with experimental validation on emoji and facial datasets.
Xiaohan Li, Yingqian Xu, Caihua Wan, Ran Zhang, Meike Hindenberg, Raik Hoffmann, Shiqiang Liu, Tianyi Zhang, Shilong Xiong, Dehao Kong, Jihao Xia, Fangshuo Gao, Zhuyang Nie, Thomas Kämpfe, Guoqiang Yu, Xiufeng Han   +15 more
wiley   +1 more source

Self-Supervised Contrastive Learning and GAN-Based Denoising for High-Fidelity HumanNeRF Images. [PDF]

Sensors (Basel)
Xu Q, Xu W, Huang M, Yan W, Guo Y.
europepmc   +1 more source

Advances in Artificial Intelligence‐Based Liver‐Related Semantic Segmentation Techniques and Applications Using CT Imaging

Cancer Medicine, Volume 15, Issue 4, April 2026.
This review summarizes clinical and technical advancements in AI‐based semantic segmentation for liver organ, tumors, and vasculature on CT imaging. It highlights key applications in surgical planning and disease evaluation while discussing critical challenges and strategies for real‐world clinical deployment and multimodal integration.
Jun Pu, Xuan Wang, Liang Zhu, Jie Pan
wiley   +1 more source