Multi-Modal Machine Learning in Engineering Design: A Review and Future Directions
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2023/11/24
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Indian UGC (journal)
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Refrences285
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Citations4
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Binyang Song Virginia Tech Department of Industrial and Systems Engineering, , Blacksburg, VA 24060
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Rui Zhou Massachusetts Institute of Technology Department of Mechanical Engineering, , Cambridge, MA 02139
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Faez Ahmed Massachusetts Institute of Technology Department of Mechanical Engineering, , Cambridge, MA 02139
Abstract
Cite
Song, Binyang, et al. “Multi-Modal Machine Learning in Engineering Design: A Review and Future Directions”. Journal of Computing and Information Science in Engineering, vol. 24, no. 1, 2023, https://doi.org/10.1115/1.4063954.
Song, B., Zhou, R., & Ahmed, F. (2023). Multi-Modal Machine Learning in Engineering Design: A Review and Future Directions. Journal of Computing and Information Science in Engineering, 24(1). https://doi.org/10.1115/1.4063954
Song, Binyang, Rui Zhou, and Faez Ahmed. “Multi-Modal Machine Learning in Engineering Design: A Review and Future Directions”. Journal of Computing and Information Science in Engineering 24, no. 1 (2023). https://doi.org/10.1115/1.4063954.
Song B, Zhou R, Ahmed F. Multi-Modal Machine Learning in Engineering Design: A Review and Future Directions. Journal of Computing and Information Science in Engineering. 2023;24(1).
Journal Categories
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
Technology
Engineering (General)
Civil engineering (General)
Technology
Manufactures
Technology
Technology (General)
Industrial engineering
Management engineering
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Three-Dimensional-Slice-Super-Resolution-Net: A Fast Few Shooting Learning Model for 3D Super-Resolution Using Slice-Up and Slice-Reconstruction | Journal of Computing and Information Science in Engineering |
| 1 | 2024 |
What’s in a Name? Evaluating Assembly-Part Semantic Knowledge in Language Models Through User-Provided Names in Computer Aided Design Files | Journal of Computing and Information Science in Engineering |
| 1 | 2024 |
DDE-GAN: Integrating a Data-Driven Design Evaluator Into Generative Adversarial Networks for Desirable and Diverse Concept Generation | Journal of Mechanical Design |
| 2 | 2023 |
Deep Learning Methods of Cross-Modal Tasks for Conceptual Design of Product Shapes: A Review | Journal of Mechanical Design |
| 6 | 2023 |
Generative Design: Reframing the Role of the Designer in Early-Stage Design Process | Journal of Mechanical Design |
| 9 | 2023 |
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
| Deep learning and tree-based models for earth skin temperature forecasting in Malaysian environments | Applied Soft Computing |
| 2024 | |
| Could AI Ethical Anxiety, Perceived Ethical Risks and Ethical Awareness About AI Influence University Students’ Use of Generative AI Products? An Ethical Perspective | International Journal of Human–Computer Interaction |
| 2024 | |
Unleashing the potential: AI empowered advanced metasurface research | Nanophotonics |
| 2024 | |
Toward Artificial Empathy for Human-Centered Design | Journal of Mechanical Design |
| 2023 |
Citations Analysis
The category
Science: Mathematics: Instruments and machines: Electronic computers. Computer science 2
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Toward Artificial Empathy for Human-Centered Design and was published in 2023. The most recent citation comes from a 2024 study titled Could AI Ethical Anxiety, Perceived Ethical Risks and Ethical Awareness About AI Influence University Students’ Use of Generative AI Products? An Ethical Perspective. This article reached its peak citation in 2024, with 3 citations. It has been cited in 4 different journals, 25% of which are open access. Among related journals, the International Journal of Human–Computer Interaction cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.