Szczegóły publikacji
Opis bibliograficzny
Supporting the process of sewer pipes inspection using machine learning on embedded devices / Mieszko Kłusek, Tomasz SZYDŁO // W: Computational Science – ICCS 2021 : 21st International Conference : Krakow, Poland, June 16–18, 2021 : proceedings, Pt. 6 / eds. Maciej Paszyński, [et al.]. — Cham : Springer Nature Switzerland, cop. 2021. — (Lecture Notes in Computer Science ; ISSN 0302-9743 ; LNCS 12747. Theoretical Computer Science and General Issues ; ISSN 0302-9743). — ISBN: 978-3-030-77979-5; e-ISBN: 978-3-030-77980-1. — S. 347–360. — Bibliogr., Abstr. — Publikacja dostępna online od: 2021-06-09
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 134763 |
|---|---|
| Data dodania do BaDAP | 2021-06-28 |
| DOI | 10.1007/978-3-030-77980-1_27 |
| Rok publikacji | 2021 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Konferencja | International Conference on Computational Science 2021 |
| Czasopisma/serie | Lecture Notes in Computer Science, Theoretical Computer Science and General Issues |
Abstract
We are currently seeing an increasing interest in using machine learning and image recognition methods to support routine human-made processes in various application domains. In the paper, the results of the conducted research on supporting the sewage network inspection process with the use of machine learning on embedded devices are presented. We analyze several image recognition algorithms on real-world data, and then we discuss the possibility of running these methods on embedded hardware accelerators.
