Results 91 to 100 of about 30,189 (295)
, 2023 This research aims to develop a method for identifying gas types based on multisensor data using Recurrent Neural Network (RNN) in the context of Electronic Nose (E-Nose) application.
Mudjirahardjo, Panca +2 more
core +1 more source
Advanced Intelligent Discovery, EarlyView.Exosomes are emerging as powerful biomarkers for disease diagnosis and monitoring. This review highlights the integration of surface‐enhanced Raman spectroscopy with artificial intelligence to enhance molecular fingerprinting of exosomes. Machine learning and deep learning techniques improve spectral interpretation, enabling accurate classification of ...
Munevver Akdeniz +2 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.A sequential deep learning framework is developed to model surface roughness progression in multi‐stage microneedle fabrication. Using real‐world experimental data from 3D printing, molding, and casting stages, an long short‐term memory‐based recurrent neural network captures the cumulative influence of geometric parameters and intermediate outputs ...
Abdollah Ahmadpour +5 more
wiley +1 more source
MUSE-RNN: a multilayer self-evolving recurrent neural network for data stream classification
, 2019 In this paper, we propose MUSE-RNN, a multilayer self-evolving recurrent neural network model for real-time classification of streaming data. Unlike the existing approaches, MUSE-RNN offers special treatment towards capturing temporal aspects of data ...
Das, M. +3 more
core +1 more source
Deep Learning‐Assisted Design of Mechanical Metamaterials
Advanced Intelligent Discovery, EarlyView.This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong +5 more
wiley +1 more source
Сучасні інформаційні системи, 2019 This paper contains formal problem definition of predicting unfavorable airborne events during flight. Restrictions and assumptions are put into the prognosis method of unfavorable airborne events during flight.
Evhenii Gryshmanov +2 more
doaj +1 more source
Recurrent Neural Network Based Narrowband Channel Prediction
, 2006 In this contribution, the application of fully connected recurrent neural networks (FCRNNs) is investigated in the context of narrowband channel prediction.
Liu, W., Yang, L-L., Hanzo, L.
core
Optical Proximity Correction Using Bidirectional Recurrent Neural Network With Attention Mechanism
, 2021 Recurrent neural network (RNN) is employed as a machine learning model for fast optical proximity correction (OPC). RNN consists of a number of neural network instances which are serially connected, with each instance in charge of one segment.
Kwon, Yonghwi, Shin, Youngsoo
core +1 more source
Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook
Advanced Intelligent Discovery, EarlyView.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
, 2021 © 2020 Elsevier Ltd Mobile devices furnish users with various services while on the move, but also raise public concerns about trajectory privacy. Unfortunately, traditional privacy protection methods, such as anonymity and generalization, are not secure
Wang, H +5 more
core +1 more source