Probabilistic context integration‐based aircraft behaviour intention classification at airport ramps

Author:

Lee Soomok1ORCID,Seo Seung‐Woo1

Affiliation:

1. Department of Electrical and Computer Engineering Seoul National University Kwanak‐to 1 Seoul Republic of Korea

Publisher

Institution of Engineering and Technology (IET)

Subject

Law,Mechanical Engineering,General Environmental Science,Transportation

Reference39 articles.

1. Accurate Tracking, Collision Detection, and Optimal Scheduling of Airport Ground Support Equipment

2. Morris R. et al.:Self‐driving aircraft towing vehicles: A preliminary report. In:Workshops at the Twenty‐Ninth AAAI Conference on Artificial Intelligence.AAAI Press Palo Alto(2015)

3. Lin T.‐Y. et al.:Microsoft coco: Common objects in context. In:European Conference on Computer Vision.Springer Cham(2014)

4. Qi C.R. Su H. Mo K. Guibas L.J.:Pointnet: Deep learning on point sets for 3d classification and segmentation. In:IEEE Conference on Computer Vision and Pattern Recognition pp. 652–660.IEEE Piscataway(2017)

5. Hu Y. Wei Z. Tomizuka M.:Probabilistic prediction of vehicle semantic intention and motion. In:2018 IEEE Intelligent Vehicles Symposium (IV).IEEE Piscataway(2018)

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