Results 31 to 40 of about 3,626 (230)

Learning Optimal Crowd Evacuation from Scratch Through Self‐Play

Advanced Intelligent Systems, EarlyView.
How would a superintelligent crowd behave in emergencies? This study develops an approach using multiagent deep reinforcement learning combined with self‐play to discover optimal evacuation strategies for pressure‐aware agents. The model learns behaviors such as queuing and zipper‐merging that significantly surpass traditional approaches in fatality ...
Mahdi Nasiri, Malte Cordts, Heinz Koeppl, Benno Liebchen   +3 more
wiley   +1 more source

Tumor Auxiliary Prediction Strategy Based on Multiscale Feature Fusion in Medical Decision‐Making System

Advanced Intelligent Systems, EarlyView.
GA: MCFFS method architecture. Pathological images are processed by the multi‐level feature information fusion (MLFF) method and the multi‐scale feature map fusion strategy to achieve the recognition result of cell nuclei. The MLFF module contains convolution blocks, spatial self‐attention, and atrous spatial pyramid pooling.
Yingqing Lu, Jing Zhou, Fangfang Gou, Jia Wu   +3 more
wiley   +1 more source

Latent Diffusion Models for Virtual Battery Material Screening and Characterization

Batteries &Supercaps, EarlyView.
A newly developed virtual tool is designed to enhance the extraction of meaningful information from characterization technique data and effectively guides the screening of target battery materials based on functional requirements. Efficient characterization of battery materials is fundamental to understanding the underlying electrochemical mechanisms ...
Deepalaxmi Rajagopal, Arnd Koeppe, Adrian Cierpka, Britta Nestler   +3 more
wiley   +1 more source

Performance Analysis of Reed-Solomon Codes Concatenated with Convolutional Codes Over AWGN Channel

, 2016
With rapid growth in today’s technology, digital communication is playing a major role to provide hostile environment to meet various applications. In this communication, Coding plays a prominent role to contribute error free transmission through channel
K. Mergu
semanticscholar   +1 more source

A 3.55‐µm Ultrathin, Skin‐Like Mechanoresponsive, Compliant, and Seamless Ionic Conductive Electrode for Epidermal Electrophysiological Signal Acquisition and Human‐Machine Interaction

Exploration, EarlyView.
The 3.55 µm ultrathin CEAB electrode is a flexible, self‐healing ionic gel with skin‐like mechanical properties, designed for stable, artifact‐free collection of electrophysiological signals during motion. This design ensures reliable long‐term monitoring for applications like depression detection via EEG, reflex arc detection, and hand gesture ...
Likun Zhang, Peiwu Qin, Huazhang Ying, Zhicheng Du, Chenying Lu, Minjiang Chen, Liyan Lei, Ziwu Song, Jiaju Chen, Xi Yuan, Canhui Yang, Vijay Pandey, Can Yang Zhang, Dongmei Yu, Peisheng He, Liwei Lin, Wenbo Ding, Xinhui Xing, Chenggang Yan, Jiansong Ji, Zhenglin Chen   +20 more
wiley   +1 more source

Totally defined nanocatalysis: Detection of polyelement nanoparticles by deep learning

InfoMat, EarlyView.
This work reports the combining STEM with deep learning with convolutional neural network of selected individual NPs of significant aspects of shape and size for widespread and commercially important PtPdInGaP@TiO2 NPs. The proposed method facilitates the detection and segmentation of HEA NPs, which has the potential for the development of high ...
Wail Al Zoubi, Manar Alnaasan, Bassem Assfour, Stefano Leoni, Iftikhar Hussain, Sungho Kim, Young Gun Ko   +6 more
wiley   +1 more source

Accelerated water residual removal in MRS: Exploring deep learning versus fitting‐based approaches

Magnetic Resonance in Medicine, EarlyView.
Abstract Purpose Removing water residual signals from MRS spectra is crucial for accurate metabolite quantification. However, currently available algorithms are computationally intensive and time‐consuming, limiting their clinical applicability. This work aims to propose and validate two novel pipelines for fast water residual removal in MRS.
Federico Turco, Johannes Slotboom, Milena Capiglioni   +2 more
wiley   +1 more source

Modeling the MRI gradient system with a temporal convolutional network: Improved reconstruction by prediction of readout gradient errors

Magnetic Resonance in Medicine, EarlyView.
Purpose Our objective is to develop a general, nonlinear gradient system model that can accurately predict gradient distortions using convolutional networks. Methods A set of training gradient waveforms were measured on a small animal imaging system and used to train a temporal convolutional network to predict the gradient waveforms produced by the ...
Jonathan B. Martin, Hannah E. Alderson, John C. Gore, Mark D. Does, Kevin D. Harkins   +4 more
wiley   +1 more source

Optimized reconstruction of undersampled Dixon sequences using new memory‐efficient unrolled deep neural networks: HalfVarNet and HalfDIRCN

Magnetic Resonance in Medicine, EarlyView.
Abstract Purpose Fat fraction (FF) quantification in individual muscles using quantitative MRI is of major importance for monitoring disease progression and assessing disease severity in neuromuscular diseases. Undersampling of MRI acquisitions is commonly used to reduce scanning time. The present paper introduces novel unrolled neural networks for the
Sandra Martin, Amira Trabelsi, Maxime Guye, Marc Dubois, Redha Abdeddaim, David Bendahan, Rémi André   +6 more
wiley   +1 more source

A Data‐Driven Approach to Integrated Adaptive Morphing and Guidance for Cruise Missiles

International Journal of Mechanical System Dynamics, EarlyView.
ABSTRACT To address the complex coupling between aerodynamic characteristics and guidance control for morphing flight missiles, this study proposes a data‐driven approach to integrated adaptive morphing and guidance. Firstly, an aerodynamic surrogate model is constructed using a fully connected neural network (FCNN), mapping the configuration ...
Ming‐Yu Wu, Jiang‐Liu Huang, Xiao‐Wei Cai, Xian‐Jun He, Zhi‐Hua Chen, Chun Zheng, Yi‐Xin Liu   +6 more
wiley   +1 more source