Results 51 to 60 of about 953 (204)
Advanced Energy Materials, EarlyView.In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu +6 more
wiley +1 more source
Datenfusion für Fahrerassistenzsysteme basierend auf der Random-Finite-Set-Statistik
, 2016 The primary aim of Advanced Driver Assistance Systems (ADAS) is to aid in improving the safety and performance of assisted driving. This is achieved using a suite of integrated sensors to detect, identify and track targets within the environment. The map
Zhang, Feihu
core
Spacecraft Relative Navigation Using Random Finite Sets [PDF]
, 2019 University of Minnesota M.S. thesis. May 2019. Major: Aerospace Engineering and Mechanics. Advisor: Richard Linares. 1 computer file (PDF); xviii, 69 pages.Future space missions require that spacecraft have onboard capability to autonomously navigate ...
Schlenker, Lauren
core
Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories
Advanced Energy Materials, EarlyView.In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen +4 more
wiley +1 more source
A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation
Advanced Intelligent Discovery, EarlyView.This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley +1 more source
Random Set Based Road Mapping using Radar Measurements
, 2010 This work is concerned with the problem of multi-sensor multi-target tracking of stationary road side objects, i.e. guard rails and parked vehicles, in the context of automotive active safety systems.
Lundquist, Christian +4 more
core +1 more source
Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion
Advanced Intelligent Discovery, EarlyView.This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia +1 more
wiley +1 more source
Online multi-object tracking via labeled random finite set with appearance learning
, 2017 © 2017 IEEE. In this paper, a novel approach to online multi-object tracking is proposed via Labeled Random Finite Sets (RFS) combined with appearance learning.
Du Yong Kim, Kim, Du Yong
core +1 more source
Advanced Intelligent Discovery, EarlyView.Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Advanced Intelligent Discovery, EarlyView.This study reveals that sampling strategy (i.e., sampling size and approach) is a foundational prerequisite for building accurate and generalizable AI models in peptide discovery. Reaching a threshold of 7.5% of the total tetrapeptide sequence space was essential to ensure reliable predictions.
Meiru Yan +3 more
wiley +1 more source