![]() ![]() King Saud University Medical City, Riyadh, SA. Editor-in-Chief Chunli Bai, Chinese Academy of Sciences, China Executive Editor-in-Chief Mu-ming Poo, Shanghai Institutes for Biological Sciences, Chinese Ac. Dartmouth College, Hanover, NH, (3) Dartmouth-Hitchcock Med. Finally, some challenges and future topics of multimodal data fusion deep learning models are described. News Editor & Managing Editor (Information Sciences) Science China Press, China. She is an Associate Professor in the Elmore Family School of Electrical and Computer Engineering at Purdue University. In 2011, Professor Jing Gao graduated with a PhD from the Grainger College of Engineering at the University of Illinois Urbana-Champaign. Then the current pioneering multimodal data fusion deep learning models are summarized. 2022 Early Career Academic Achievement Alumni Award. Specifically, representative architectures that are widely used are summarized as fundamental to the understanding of multimodal deep learning. Thus, this review presents a survey on deep learning for multimodal data fusion to provide readers, regardless of their original community, with the fundamentals of multimodal deep learning fusion method and to motivate new multimodal data fusion techniques of deep learning. 5 Key Laboratory of Drug Research & Centre of Pharmaceutics, Shanghai Institute of Materia Medica, Chinese Academy of Sciences, Shanghai, 201203, China. 4 Graduate School of Biomedical Engineering, University of New South Wales, Sydney, NSW, 2052, Australia. With the increasing exploration of the multimodal big data, there are still some challenges to be addressed. 3 School of Pharmacy, Nantong University, Nantong, 226001, China. The Geisel School of Medicine has 885 full-time faculty on staff. In this review, we present some pioneering deep learning models to fuse these multimodal big data. The faculty-student ratio at Dartmouth College (Geisel) is 2.4:1. ![]() These data, referred to multimodal big data, contain abundant intermodality and cross-modality information and pose vast challenges on traditional data fusion methods. Four former surgeons general met with undergraduate and graduate students across Dartmouth on Wednesday afternoon to discuss mental health, wellness, and higher education. With the wide deployments of heterogeneous networks, huge amounts of data with characteristics of high volume, high variety, high velocity, and high veracity are generated. ![]()
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