Physiological Monitoring Applications of Wearable Multimodal Fusion Systems Based on ECG and PPG: A Comprehensive Review [PDF]
SensorsWearable technology has become popular today not only for clinical uses but also among the general public for everyday activities such as fitness tracking and activity recognition. It’s no secret that wearable devices need to be more comfortable and that
Chamod Rathnayake +3 more
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Effective Techniques for Multimodal Data Fusion: A Comparative Analysis
Sensors, 2023 Data processing in robotics is currently challenged by the effective building of multimodal and common representations. Tremendous volumes of raw data are available and their smart management is the core concept of multimodal learning in a new paradigm ...
Maciej Pawłowski +2 more
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Multimodal Data Fusion in Learning Analytics: A Systematic Review
Sensors, 2020 Multimodal learning analytics (MMLA), which has become increasingly popular, can help provide an accurate understanding of learning processes. However, it is still unclear how multimodal data is integrated into MMLA.
Su Mu, Meng Cui, Xiaodi Huang
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Survey of Research on Multimodal Fusion Technology for Deep Learning [PDF]
Jisuanji gongcheng, 2020 Multimodal Fusion Technology(MFT) for Deep Learning(DL) refers to the conversion and fusion of information obtained by machine from texts,images,voices,videos and other materials,so as to improve the performance of the model.The universality of modals ...
HE Jun, ZHANG Caiqing, LI Xiaozhen, ZHANG Dehai
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2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), 2023 Accepted by 6th Multi-Modal Learning and Applications Workshop (MULA), CVPR 2023.
Zihui Xue, Radu Marculescu
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Multiscale Efficient Channel Attention for Fusion Lane Line Segmentation
Complexity, 2021 The use of multimodal sensors for lane line segmentation has become a growing trend. To achieve robust multimodal fusion, we introduced a new multimodal fusion method and proved its effectiveness in an improved fusion network.
Kang Liu, Xin Gao
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AFR-BERT: Attention-based mechanism feature relevance fusion multimodal sentiment analysis model
PLoS ONE, 2022 Multimodal sentiment analysis is an essential task in natural language processing which refers to the fact that machines can analyze and recognize emotions through logical reasoning and mathematical operations after learning multimodal emotional features.
Ji Mingyu, Zhou Jiawei, Wei Ning
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MCR: Multilayer cross‐fusion with reconstructor for multimodal abstractive summarisation
IET Computer Vision, 2023 Multimodal abstractive summarisation (MAS) aims to generate a textual summary from multimodal data collection, such as video‐text pairs. Despite the success of recent work, the existing methods lack a thorough analysis for consistency across multimodal ...
Jingshu Yuan +4 more
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Reducing Annotation Burden Through Multimodal Learning
Frontiers in Big Data, 2020 Choosing an optimal data fusion technique is essential when performing machine learning with multimodal data. In this study, we examined deep learning-based multimodal fusion techniques for the combined classification of radiological images and ...
Kevin Lopez +5 more
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Multimodal Fusion: A Review, Taxonomy, Open Challenges, Research Roadmap and Future Directions [PDF]
Neutrosophic Sets and Systems, 2021 The present work collects a plethora of previous research work in the field of multimodal fusion which despite a lot of research could not handle the imperfections.
Mohd Anas Wajid, Aasim Zafar
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