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Special Issue "Deep Learning Based Sensing Technologies for Autonomous Vehicles"
Deadline for manuscript submissions: closed (15 February 2019).
Interests: sensor networks; mobile computing; network coding; machine learning
Special Issues and Collections in MDPI journals
Special Issue in Sensors: Selected Papers from the Eighth International Conference on ICT Convergence (ICTC 2017)
Special Issue in Sensors: Multimedia Data Applications in Wireless Sensor Networks
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Interests: machine learning and control systems; mobile sensor networks; autonomous vehicles and robots; biomedical engineering
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Interests: machine learning and signal processing applied to audio and music
We are witnessing the era of self-driving vehicles and autonomous robots: Autonomous vehicles and robots are becoming indispensable parts of everyday life. The heart of the vehicle, with a high degree of autonomy, are the various sensing algorithms and devices weaved into its platform, providing perception capabilities. Recent advances in such deep learning sensing technologies are realizing the autonomous vehicle era; however, there are still many intriguing research problems and concerns on robustness under uncertainties. Deep neural network based sensor fusion techniques that fuse different modalities for different tasks, such as self-driving, intention learning, situation awareness, and risk assessment become more important. Additionally, intelligent or active sensing, with autonomous decision-making and control, has gained wide attention. This Special Issue is focused on such sensing technologies for autonomous vehicles and robots with an emphasis on deep learning based sensing algorithms. The topics of interest include, but not limited to:
- Deep learning based perception algorithms for autonomous vehicles and robots
- Deep learning based sensor fusion for multimodal sensors
- Sensing algorithms for intention learning, situation awareness, and risk assessment
- Emerging sensor technologies for autonomous vehicles and robots
- Bayesian algorithms and Gaussian process regression for sensor fusion
- V2V/V2X technologies for inter-vehicle sensor fusion
- Deep learning based end-to-end control for autonomous vehicles and robots
Prof. Joon-Sang Park
Prof. Jongeun Choi
Prof. Kyogu Lee
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sensors is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 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.
- Deep Learning
- Machine perception
- Sensor fusion
- Autonomous vehicles