Neural network learning to identify airport runway taxiway numbers

Zhi Ha Chen, Jyh-Chin Juang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

In order to reduce the number of 'Runway Incursion' crashes, the process and method of the study is to simulate human visual neuron recognition pictures and train a machine learning model. The results are modeled as follows:1. The neural network outputs the feature vectors model after the Convolution operation. 2. Filter is used to detect the pixels of the background image of the airport environment. The feature map is output with Activated feature map. The same weight of the same feature object is added with Max pooling layer after convolution layer to find the feature map more obvious. We can use Deep Learning to simulate the Artificial Intelligence model environment instead of manual recognition, simulate Drone to recognize the runway number automatically and drive into the tower path planning runway area correctly. Specific images such as runway numbers, area locations, etc., provide an unexpectedly increased opportunity to resolve the 'Runway Incursion' case.

Original languageEnglish
Title of host publicationProceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages153-157
Number of pages5
ISBN (Electronic)9781538670361
DOIs
Publication statusPublished - 2019 Feb 19
Event4th International Symposium on Computer, Consumer and Control, IS3C 2018 - Taichung, Taiwan
Duration: 2018 Dec 62018 Dec 8

Publication series

NameProceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018

Conference

Conference4th International Symposium on Computer, Consumer and Control, IS3C 2018
CountryTaiwan
CityTaichung
Period18-12-0618-12-08

Fingerprint

Airport runways
Neural Networks
Neural networks
Convolution
Pooling
Output
Path Planning
Crash
Motion planning
Feature Vector
Airports
Towers
Neurons
Artificial intelligence
Learning systems
Neuron
Artificial Intelligence
Resolve
Machine Learning
Pixel

All Science Journal Classification (ASJC) codes

  • Computer Networks and Communications
  • Control and Systems Engineering
  • Energy Engineering and Power Technology
  • Computer Science Applications
  • Control and Optimization
  • Signal Processing

Cite this

Chen, Z. H., & Juang, J-C. (2019). Neural network learning to identify airport runway taxiway numbers. In Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018 (pp. 153-157). [8644759] (Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IS3C.2018.00046
Chen, Zhi Ha ; Juang, Jyh-Chin. / Neural network learning to identify airport runway taxiway numbers. Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018. Institute of Electrical and Electronics Engineers Inc., 2019. pp. 153-157 (Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018).
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Chen, ZH & Juang, J-C 2019, Neural network learning to identify airport runway taxiway numbers. in Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018., 8644759, Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018, Institute of Electrical and Electronics Engineers Inc., pp. 153-157, 4th International Symposium on Computer, Consumer and Control, IS3C 2018, Taichung, Taiwan, 18-12-06. https://doi.org/10.1109/IS3C.2018.00046

Neural network learning to identify airport runway taxiway numbers. / Chen, Zhi Ha; Juang, Jyh-Chin.

Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018. Institute of Electrical and Electronics Engineers Inc., 2019. p. 153-157 8644759 (Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Chen ZH, Juang J-C. Neural network learning to identify airport runway taxiway numbers. In Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018. Institute of Electrical and Electronics Engineers Inc. 2019. p. 153-157. 8644759. (Proceedings - 2018 International Symposium on Computer, Consumer and Control, IS3C 2018). https://doi.org/10.1109/IS3C.2018.00046