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ETD Abstract Container

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Deep Learning for Sensor Fusion

Howard, Shaun Michael
http://orcid.org/0000-0003-0341-7349
http://rave.ohiolink.edu/etdc/view?acc_num=case1495751146601099

Abstract Details

2017, Master of Sciences (Engineering), Case Western Reserve University, EECS - Computer and Information Sciences.
The use of multiple sensors in modern day vehicular applications is necessary to provide a complete outlook of surroundings for advanced driver assistance systems (ADAS) and automated driving. The fusion of these sensors provides increased certainty in the recognition, localization and prediction of surroundings. A deep learning-based sensor fusion system is proposed to fuse two independent, multi-modal sensor sources. This system is shown to successfully learn the complex capabilities of an existing state-of-the-art sensor fusion system and generalize well to new sensor fusion datasets. It has high precision and recall with minimal confusion after training on several million examples of labeled multi-modal sensor data. It is robust, has a sustainable training time, and has real-time response capabilities on a deep learning PC with a single NVIDIA GeForce GTX 980Ti graphical processing unit (GPU).
Wyatt Newman, Dr (Committee Chair)
M. Cenk Cavusoglu, Dr (Committee Member)
Michael Lewicki, Dr (Committee Member)
171 p.
Artificial Intelligence; Computer Science
deep learning; sensor fusion; deep neural networks; advanced driver assistance systems; automated driving; multi-stream neural networks; feedforward; multilayer perceptron; recurrent; gated recurrent unit; long-short term memory; camera; radar;

Recommended Citations

Citations

  • Howard, S. M. (2017). Deep Learning for Sensor Fusion [Master's thesis, Case Western Reserve University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=case1495751146601099

    APA Style (7th edition)

  • Howard, Shaun. Deep Learning for Sensor Fusion. 2017. Case Western Reserve University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=case1495751146601099.

    MLA Style (8th edition)

  • Howard, Shaun. "Deep Learning for Sensor Fusion." Master's thesis, Case Western Reserve University, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=case1495751146601099

    Chicago Manual of Style (17th edition)

case1495751146601099
9,892
© 2017, all rights reserved.
This open access ETD is published by Case Western Reserve University School of Graduate Studies and OhioLINK.