Multimodal Context Fusion
Multimodal Context Fusion is a context-aware fusion method that integrates heterogeneous contextual data from multiple modalities—such as visual, auditory, spatial, and physiological inputs—through synchronized feature-level or decision-level fusion to enhance situation awareness and adaptive response in augmented reality environments.
24
Publications
1.6K
Citations
106
Authors
57
Institutions
Publications per year
2017–2026
17
24
Bridging Search Region Interaction with Template for RGB-T Tracking
Tianrui Hui, Zizheng Xun, Fengguang Peng et al. · 2023 · 122 citations
Making of Night Vision: Object Detection Under Low-Illumination
Yuxuan Xiao, Aiwen Jiang, Jihua Ye et al. · IEEE Access · 2020 · 117 citations · Full text
A novel context-aware multimodal framework for persian sentiment analysis
Kia Dashtipour, Mandar Gogate, Erik Cambria et al. · Neurocomputing · 2021 · 96 citations · Full text
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University of California San Diego
San Diego, United States
3 h-index
6 publications
62 citations

United States Air Force Research Laboratory
Wright-Patterson AFB, United States
2 h-index
4 publications
219 citations
Xiamen University
Xiamen, China
1 h-index
3 publications
168 citations
Intelligent Fusion Technology (United States)
Germantown, United States
1 h-index
3 publications
204 citations
Blackberry (United States)
Pleasanton, United States
1 h-index
1 publications
12 citations
Deutsche Telekom (Singapore)
Singapore, Singapore
1 h-index
2 publications
78 citations
Oregon Health & Science University
Portland, United States
1 h-index
3 publications
60 citations

University of Rochester
Rochester, United States
1 h-index
2 publications
112 citations
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Repository · 3 publications · 47 citations
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1 publications · 10 citations
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1 publications · 96 citations
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1 publications · 37 citations
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1 publications · 117 citations
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