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A survey on machine learning for data fusion
Information Fusion, 2020 Data fusion is a prevalent way to deal with imperfect raw data for capturing reliable, valuable and accurate information. Comparing with a range of classical probabilistic data fusion techniques, machine learning method that automatically learns from ...
Tong Meng +3 more
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ACM Computing SurveysMultimodal Artificial Intelligence (Multimodal AI), in general, involves various types of data (e.g., images, texts, or data collected from different sensors), feature engineering (e.g., extraction, combination/fusion), and decision-making (e.g ...
Fei Zhao, Chengcui Zhang, Baocheng Geng
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Advances in multimodal data fusion in neuroimaging: Overview, challenges, and novel orientation
Information Fusion, 2020 Highlights • We analysed over 450 references from all well-famed databases.• We provided a comprehensive survey on multimodal data fusion in neuroimaging.• This review encompassed current challenges & applications, strengths &limitations.• Fundamental ...
Yudong Zhang +11 more
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Deep Learning in Multimodal Remote Sensing Data Fusion: A Comprehensive Review [PDF]
International Journal of Applied Earth Observation and Geoinformation, 2022 With the extremely rapid advances in remote sensing (RS) technology, a great quantity of Earth observation (EO) data featuring considerable and complicated heterogeneity is readily available nowadays, which renders researchers an opportunity to tackle ...
Jiaxin Li +6 more
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Effective Techniques for Multimodal Data Fusion: A Comparative Analysis [PDF]
Italian National Conference on Sensors, 2022 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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Unbox the black-box for the medical explainable AI via multi-modal and multi-centre data fusion: A mini-review, two showcases and beyond [PDF]
Information Fusion, 2021 Explainable Artificial Intelligence (XAI) is an emerging research topic of machine learning aimed at unboxing how AI systems’ black-box choices are made. This research field inspects the measures and models involved in decision-making and seeks solutions
Guang Yang, Qinghao Ye, Jun Xia
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Multimodal deep learning for biomedical data fusion: a review
Briefings Bioinform., 2022 Biomedical data are becoming increasingly multimodal and thereby capture the underlying complex relationships among biological processes. Deep learning (DL)-based data fusion strategies are a popular approach for modeling these nonlinear relationships ...
S. Stahlschmidt +2 more
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UAV-based multi-sensor data fusion and machine learning algorithm for yield prediction in wheat
Precision Agriculture, 2022 Early prediction of grain yield helps scientists to make better breeding decisions for wheat. Use of machine learning (ML) methods for fusion of unmanned aerial vehicle (UAV)-based multi-sensor data can improve the prediction accuracy of crop yield.
Shuaipeng Fei +8 more
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Rice-Fusion: A Multimodality Data Fusion Framework for Rice Disease Diagnosis
IEEE Access, 2022 Rice leaf infections are a common hazard to rice production, affecting many farmers all over the world. Early detection and treatment of rice leaf infection are critical for promoting healthy rice plant growth and ensuring adequate supply for the fast ...
R. Patil, Sumit Kumar
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Multi-Source Multi-Domain Data Fusion for Cyberattack Detection in Power Systems [PDF]
IEEE Access, 2021 Modern power systems equipped with advanced communication infrastructure are cyber-physical in nature. The traditional approach of leveraging physical measurements for detecting cyber-induced physical contingencies is insufficient to reflect the accurate
Abhijeet Sahu +6 more
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