Machine Learning and Deep Learning for Multisensor Data Fusion and Integration

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: 25 May 2024 | Viewed by 256

Special Issue Editor


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Guest Editor
College of Computer Science and Engineering, Shandong University of Science and Technology, Qingdao 266510, China
Interests: multimedia processing; sensor fusion; machine learning; information hiding
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Special Issue Information

Dear Colleagues,

Multisensor tools, e.g., intelligent vision and autonomous navigation, have been increasingly applied in unmanned equipment, wherein sensor data fusion is a key issue. Many theories, methods and techniques have been developed to confront this challenge in recent years. Deep learning and metaheuristic optimization may promote the application of machine learning in image and speech recognition. However, data fusion and analysis methods must be further studied. This Special Issue discusses the relative design and analysis of learning networks and algorithms of deep learning for multisensor data fusion with applications in unmanned equipment. Topics of interest for publication include, but are not limited to:

  • Multisensor fusion theory;
  • Deep learning networks for multisensor tools;
  • Machine learning for multisensor tools;
  • Sensor signal processing for unmanned equipment.

Prof. Dr. Jeng-Shyang Pan
Guest Editor

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • multisensor fusion
  • sensor fusion
  • deep learning
  • machine learning
  • unmanned equipment

Published Papers

This special issue is now open for submission.
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