Artificial intelligence-assisted data fusion

Xuyin Ding; Yecheng Zhang; Hossam Haick; Min Zhang

doi:10.1016/B978-0-443-15684-7.00042-7

Artificial intelligence-assisted data fusion

Xuyin Ding
, Yecheng Zhang
, Hossam Haick
, Min Zhang

化学与分子工程学院

East China Normal University
Technion-Israel Institute of Technology
Tsinghua University

科研成果: 书/报告/会议事项章节 › 章节 › 同行评审

2 引用（Scopus）

摘要

Data fusion is capable of addressing imperfect raw data by fusing reliable, valuable and accurate information. Artificial intelligence (AI) methods are significantly advantageous for analyzing and fusing large-scale datasets from multiple sources and/or modalities. In this chapter, we will discuss AI-assisted data fusion beginning with data acquisition to AI algorithms, data fusion methods, and the applications and challenges of contemporary AI for data fusion.

源语言	英语
主期刊名	Nature-Inspired Sensors
出版商	Elsevier
页	549-560
页数	12
ISBN（电子版）	9780443156847
ISBN（印刷版）	9780443156854
DOI	https://doi.org/10.1016/B978-0-443-15684-7.00042-7
出版状态	已出版 - 1 1月 2024

访问文件

10.1016/B978-0-443-15684-7.00042-7

其它文件与链接

链接到 Scopus 的出版物

引用此

@inbook{76020d6e581e455cb4855d076992a3d1,

title = "Artificial intelligence-assisted data fusion",

abstract = "Data fusion is capable of addressing imperfect raw data by fusing reliable, valuable and accurate information. Artificial intelligence (AI) methods are significantly advantageous for analyzing and fusing large-scale datasets from multiple sources and/or modalities. In this chapter, we will discuss AI-assisted data fusion beginning with data acquisition to AI algorithms, data fusion methods, and the applications and challenges of contemporary AI for data fusion.",

keywords = "Artificial intelligence, data acquisition, data fusion",

author = "Xuyin Ding and Yecheng Zhang and Hossam Haick and Min Zhang",

year = "2024",

month = jan,

day = "1",

doi = "10.1016/B978-0-443-15684-7.00042-7",

language = "英语",

isbn = "9780443156854",

pages = "549--560",

booktitle = "Nature-Inspired Sensors",

publisher = "Elsevier",

address = "荷兰",

}

TY - CHAP

T1 - Artificial intelligence-assisted data fusion

AU - Ding, Xuyin

AU - Zhang, Yecheng

AU - Haick, Hossam

AU - Zhang, Min

PY - 2024/1/1

Y1 - 2024/1/1

N2 - Data fusion is capable of addressing imperfect raw data by fusing reliable, valuable and accurate information. Artificial intelligence (AI) methods are significantly advantageous for analyzing and fusing large-scale datasets from multiple sources and/or modalities. In this chapter, we will discuss AI-assisted data fusion beginning with data acquisition to AI algorithms, data fusion methods, and the applications and challenges of contemporary AI for data fusion.

AB - Data fusion is capable of addressing imperfect raw data by fusing reliable, valuable and accurate information. Artificial intelligence (AI) methods are significantly advantageous for analyzing and fusing large-scale datasets from multiple sources and/or modalities. In this chapter, we will discuss AI-assisted data fusion beginning with data acquisition to AI algorithms, data fusion methods, and the applications and challenges of contemporary AI for data fusion.

KW - Artificial intelligence

KW - data acquisition

KW - data fusion

UR - https://www.scopus.com/pages/publications/85213181292

U2 - 10.1016/B978-0-443-15684-7.00042-7

DO - 10.1016/B978-0-443-15684-7.00042-7

M3 - 章节

AN - SCOPUS:85213181292

SN - 9780443156854

SP - 549

EP - 560

BT - Nature-Inspired Sensors

PB - Elsevier

ER -