Transfer Learning with CLIP Model for Multitasking Workload Prediction in Mixed Reality Environments Article Swipe
Safanah Abbas
,
Heejin Jeong
,
David He
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.5772/intechopen.1011699
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.5772/intechopen.1011699
Multitasking has become an important part of our modern life, especially when interacting with new technologies such as mixed reality (MR). Predicting human workload in MR environments is crucial for optimizing the user experience. This study adopts transfer learning for workload prediction and employs a generative model to expand the original collected dataset. A dataset has been collected from a multitasking experiment involving 36 participants, combining a real-world block-matching task and a virtual N-back task, with workload ratings recorded using the NASA task load index (NASA-TLX). The dataset was augmented by using the generative adversarial networks (GANs) model, resulting in 5000 synthesized observations. A hybrid workload prediction model integrating the contrastive language-image pre-training (CLIP) model, adapted from computer vision applications, achieved superior results with a root mean square error (RMSE) of 0.96, significantly outperforming traditional regression models. These findings highlight the potential of transfer learning in workload prediction, paving the way for more efficient human performance modeling in such hybrid environments.
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Metadata
- Type
- book-chapter
- Language
- en
- Landing Page
- https://doi.org/10.5772/intechopen.1011699
- https://www.intechopen.com/citation-pdf-url/1224193
- OA Status
- hybrid
- References
- 42
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4412823755
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4412823755Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5772/intechopen.1011699Digital Object Identifier
- Title
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Transfer Learning with CLIP Model for Multitasking Workload Prediction in Mixed Reality EnvironmentsWork title
- Type
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book-chapterOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-07-29Full publication date if available
- Authors
-
Safanah Abbas, Heejin Jeong, David HeList of authors in order
- Landing page
-
https://doi.org/10.5772/intechopen.1011699Publisher landing page
- PDF URL
-
https://www.intechopen.com/citation-pdf-url/1224193Direct link to full text PDF
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://www.intechopen.com/citation-pdf-url/1224193Direct OA link when available
- Concepts
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Human multitasking, Workload, Computer science, Transfer of learning, Human–computer interaction, Transfer (computing), Artificial intelligence, Psychology, Operating system, Cognitive psychologyTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- References (count)
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10Other works algorithmically related by OpenAlex
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