Results 121 to 130 of about 5,472,482 (287)

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

Advanced 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

Video Refereeing Model of Soccer Match Based on Fuzzy Clustering and Cuckoo Optimization Algorithm

IEEE Access
Computer technology has rapidly advanced the use of computer-assisted refereeing in sports. However, motion image segmentation presents several challenges, including image blurring due to high-speed motion and the impact of ambient light on image ...
Ting Wang, Jinglong Geng, Jing Wang, Xiao Yan   +3 more
doaj   +1 more source

A Generative AI Framework to Predict Cardiomyocyte Contraction Function From Single Static Images

Advanced Intelligent Discovery, EarlyView.
A single static hiPSC‐cardiomyocyte image is fed into a U‐Net‐GAN framework, which directly predicts a pixel‐resolved contraction heatmap without time‐lapse imaging. StyleGAN2‐generated synthetic cell–heatmap pairs augment training, improving prediction fidelity (SSIM = 0.84).
Andrew Kowalczewski, Chenyan Wang, Xinrui Wang, Huaxiao Yang, Zhao Qin, Zhen Ma   +5 more
wiley   +1 more source

Interactive Prompt‐Guided Robotic Grasping for Arbitrary Objects Based on Promptable Segment Anything Model and Force‐Closure Analysis

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
A laser pointer‐guided robotic grasping method for arbitrary objects based on promptable segment anything model and force‐closure analysis is presented. Grasp generation methods based on force‐closure analysis can calculate the optimal grasps for objects through their appearances. However, the limited visual perception ability makes robots difficult to
Yan Liu, Yaxin Liu, Ruiqing Han, Kai Zheng, Yufeng Yao, Ming Zhong   +5 more
wiley   +1 more source

Fuzzy Probability Spaces and Their Applications in Decision Matrices

, 2008
In this paper, two types of fuzzy probability spaces will be introduced and their possible applications in methods of decision-making under risk will be described. First, a fuzzy probability space that generalizes the classical probability space (ℜ n, Bn,

core  

Robust Reinforcement Learning Control Framework for a Quadrotor Unmanned Aerial Vehicle Using Critic Neural Network

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Quadrotor unmanned aerial vehicle control is critical to maintain flight safety and efficiency, especially when facing external disturbances and model uncertainties. This article presents a robust reinforcement learning control scheme to deal with these challenges.
Yu Cai, Yefeng Yang, Tao Huang, Boyang Li   +3 more
wiley   +1 more source

Machine Learning‐Based Estimation of Experimental Artifacts and Image Quality in Fluorescence Microscopy

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
The use of image quality metrics in combination with machine learning enables automatic image quality assessment for fluorescence microscopy images. The method can be integrated into the experimental pipeline for optical microscopy and utilized to classify artifacts in experimental images and to build quality rankings with a reference‐free approach ...
Elena Corbetta, Thomas Bocklitz
wiley   +1 more source

Using the Karush-Kuhn-Tucher Optimization Method on a Finite Fuzzy Markov Chain

مجلة بغداد للعلوم
It is highly interesting to explore the implications of Markov chain stability because its importance in engineering, dynamic systems, energy subject and decision-making issues.
Marwan S. Jameel, Zeiad Yahya Ali Allawee, Rana Z Al-Kawaz, Sura J Hussein   +3 more
doaj   +1 more source

Ecoefficiency Analysis and Regression in Data Conversion for Spiking Neural Network Training

Advanced Intelligent Systems, EarlyView.
The environmental footprint of spiking neural networks is quantified during dataset encoding and training for autonomous driving regression across three benchmarks. Temporal depth emerges as the dominant driver of energy consumption and CO2 emissions, while the accuracy–energy trade‐off proves dataset‐dependent. On conventional hardware, spiking models
Fernando S. Martínez, Raúl Parada, Jordi Casas‐Roma, Laia Subirats   +3 more
wiley   +1 more source

Sports Activity Recognition Using Textile‐Based Sensor Fusion and Complex‐Valued Residual Convolutional Neural Networks

Advanced Intelligent Systems, EarlyView.
Motion artifacts in electrocardiographic signals, conventionally dismissed as noise, are shown to encode discriminative activity information. A smart t‐shirt fusing textile strain sensors with textile ECG electrodes, processed through a complex‐valued residual network, recognizes 12 sport activities.
Nada Al‐azzawi, Munire Sibel Cetin, Asli Tuncay Atalay, Ozgur Atalay, Gökhan Ince   +4 more
wiley   +1 more source