Results 181 to 190 of about 2,754 (255)

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Multiscale and Multi‐Timestep Switching of Multiple Machine Learning Force Fields for Artificial Intelligence‐Driven Materials Simulations

open access: yesAdvanced Intelligent Discovery, EarlyView.
Deep Potential model switching accelerates molecular dynamics by using a faster 4 Å model for most timesteps and periodically applying a high‐accuracy 6 Å model. Validation on solid TiO2 and liquid PEG shows preserved RDF correlations and stable NPT behavior, while NVE energy‐drift analyses identify cases requiring additional validation.
Ryuya Kanda   +6 more
wiley   +1 more source

A Hybrid Transfer Learning Framework for Brain Tumor Diagnosis

open access: yesAdvanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A novel hybrid transfer learning approach for brain tumor classification achieves 99.47% accuracy using magnetic resonance imaging (MRI) images. By combining image preprocessing, ensemble deep learning, and explainable artificial intelligence (XAI) techniques like gradient‐weighted class activation mapping and SHapley Additive exPlanations (SHAP), the ...
Sadia Islam Tonni   +11 more
wiley   +1 more source

Human‐in‐the‐Loop Object Segmentation for 3D Gaussian Splatting via Finger‐based VR Interface

open access: yesAdvanced Intelligent Systems, EarlyView.
This study introduces a human‐in‐the‐loop segmentation framework for 3D Gaussian Splatting that integrates real‐time optimization with intuitive VR‐based finger prompting. Compared with existing automatic, learning‐based methods, it achieves significantly higher accuracy and reduced segmentation time.
Yongseok Lee   +5 more
wiley   +1 more source

A Memristor‐Based In‐Memory Computing System‐on‐Chip with Efficient Depthwise Convolution

open access: yesAdvanced Intelligent Systems, EarlyView.
We present a memristor‐based in‐memory computing (IMC) architecture that enables efficient depthwise convolution (DWC) acceleration. Fabricated in a system‐on‐chip with crossbar arrays, the design improves memory utilization. Experimental validation demonstrates the first hardware acceleration of DWC in IMC, achieving a digital comparable inference ...
Wenhao Song   +21 more
wiley   +1 more source

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