Publication detail

Determination of Air Jet Shape with Complex Methods Using Neural Networks

ŠŤASTNÝ, J. RICHTER, J. JURÁNEK, L.

Original Title

Determination of Air Jet Shape with Complex Methods Using Neural Networks

Type

book chapter

Language

English

Original Abstract

This article deals with the computer evaluation of airflow images. The airflow is visualized by continuous gas fibers, as for example smoke, fog or another visible additive. One of the most important properties of airflow is the shape of the stream. The principle of determining the shape of the stream is the detection of the additive. For 2D images with a heterogeneous background, it may be very difficult to distinguish the additive from the environment. This paper deals with the possibility of detecting an additive in airflow images with a heterogeneous back-ground. Artificial neural networks will be used for this purpose.

Keywords

Additive detection; Air jet shape; Airflow; Artificial neural networks; Image processing

Authors

ŠŤASTNÝ, J.; RICHTER, J.; JURÁNEK, L.

Released

1. 3. 2021

Publisher

Springer Nature Switzerland

ISBN

978-3-030-61658-8

Book

Studies in Fuzziness and Soft Computing

Pages from

25

Pages to

40

Pages count

16

URL

https://link.springer.com/chapter/10.1007/978-3-030-61659-5_3

BibTex

@inbook{BUT171189,
  author="Jiří {Šťastný} and Jan {Richter} and Luboš {Juránek}",
  title="Determination of Air Jet Shape with Complex Methods Using Neural Networks",
  booktitle="Studies in Fuzziness and Soft Computing",
  year="2021",
  publisher="Springer Nature Switzerland",
  pages="25--40",
  doi="10.1007/978-3-030-61659-5\{_}3",
  isbn="978-3-030-61658-8",
  url="https://link.springer.com/chapter/10.1007/978-3-030-61659-5_3"
}