Results 181 to 190 of about 183,434 (340)
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang +4 more
wiley +1 more source
Lightweight dual-watermarking framework for medical image authentication and integrity preservation. [PDF]
Taj R +5 more
europepmc +1 more source
This study introduces a tree‐based machine learning approach to accelerate USP8 inhibitor discovery. The best‐performing model identified 100 high‐confidence repurposable compounds, half already approved or in clinical trials, and uncovered novel scaffolds not previously studied. These findings offer a solid foundation for rapid experimental follow‐up,
Yik Kwong Ng +4 more
wiley +1 more source
DNA StairLoop: enabling high-fidelity data recovery and robust error correction in DNA-based data storage. [PDF]
Yan Z, Qu G, Chen X, Zheng G, Wu H.
europepmc +1 more source
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang +3 more
wiley +1 more source
Predictive coding narrows the gap between convolutional networks and human brain function in misspelled-word reading [PDF]
Jiaxin You +2 more
openalex +1 more source
Convolutional Neural Networks to Enhance Coded Speech [PDF]
Ziyue Zhao, Huijun Liu, Tim Fingscheidt
openalex +1 more source
Application of convolutional neural networks in focused ion beam scanning electron microscopy image denoising. [PDF]
Xu W +6 more
europepmc +1 more source
This paper presents a computer vision (deep learning) pipeline integrating YOLOv8 and YOLOv9 for automated detection, segmentation, and analysis of rosette cellulose synthase complexes in freeze‐fracture electron microscopy images. The study explores curated dataset expansion for model improvement and highlights pipeline accuracy, speed ...
Siri Mudunuri +6 more
wiley +1 more source

