Cited by 101Multimodal Machine Learning ApplicationsAdvanced Image Fusion TechniquesData Mining and Machine Learning Applications

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Multimodal data fusion for systems improvement: A review

Gaw, Nathan, Yousefi, Safoora, Gahrooei, Mostafa Reisi·2022·IISE Transactions

DOI 10.1080/24725854.2021.1987593

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Abstract

In recent years, information available from multiple data modalities has become increasingly common for industrial engineering and operations research applications. There have been a number of research works combining these data in unsupervised, supervised, and semi-supervised fashions that have addressed various issues of combining heterogeneous data, as well as several existing open challenges that remain to be addressed. In this review paper, we provide an overview of some methods for the fusion of multimodal data. We provide detailed real-world examples in manufacturing and medicine, introduce early, late, and intermediate fusion, as well as discuss several approaches under decomposition-based and neural network fusion paradigms. We summarize the capabilities and limitations of these methods and conclude the review article by discussing the existing challenges and potential research opportunities.

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Authors: Gaw, N., Yousefi, S., & Gahrooei, M. R.
Affiliations: Wright-Patterson Air Force Base (US)
Microsoft (United States) (US)
University of Florida (US)
Corresponding author: Gahrooei, Mostafa Reisi
ORCID: Gaw, Nathan
Yousefi, Safoora
Gahrooei, Mostafa Reisi
Venue: IISE Transactions
Publisher: Informa UK Limited
Published: 2021-12-03
Volume: 54
Issue: 11
Pages: 1098-1116
ISSN: 2472-5854 (ISSN-L)
2472-5862
DOI: 10.1080/24725854.2021.1987593
OpenAlex: W3210892971
Cited by: 101
References: 119
Citations by year: 2026: 20 · 2025: 28 · 2024: 33 · 2023: 14 · 2022: 5 · 2021: 1
FWCI: 4.77
Type: journal article
Language: en
Open access: closed
Locations: IISE Transactions (publishedVersion)
RePEc: Research Papers in Economics (submittedVersion)
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Multimodal Machine Learning Applications
Physical Sciences › Engineering › Media Technology › Advanced Image Fusion Techniques
Physical Sciences › Computer Science › Information Systems › Data Mining and Machine Learning Applications
Keywords: multimodal fusion, data heterogeneity, feature-level fusion, decision fusion, intermediate fusion, neural network fusion, manufacturing industry, health data, industrial engineering, operations research

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Multimodal data fusion for systems improvement: A review

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