Wykaz publikacji wybranego autora

Daniel Dworak, mgr inż.

Faculty of Electrical Engineering, Automatics, Computer Science and Biomedical Engineering
WEAIiIB-kair

Identyfikatory Autora
ORCID: 0000-0002-8013-8469 połącz konto z ORCID ResearcherID: GAZ-9630-2022 Scopus: 57778741400

Identyfikatory Autora

ORCID: 0000-0002-8013-8469 połącz konto z ORCID

ResearcherID: GAZ-9630-2022

Scopus: 57778741400

wydruk:

sortowanie:

1

Automotive radar detection level modeling with neural networks
Automotive radar detection level modeling with neural networks / Filip CIEPIELA, Mateusz Karol NOWAK, Daniel DWORAK, Mateusz Komorkiewicz // W: Advanced, contemporary control : proceedings of the XXI Polish Control Conference, Gliwice, Poland, 2023, Vol. 2 / eds. Marek Pawelczyk, [et al.]. — Cham : Springer Nature Switzerland, cop. 2023. — (Lecture Notes in Networks and Systems ; ISSN 2367-3370 ; LNNS 709). — ISBN: 978-3-031-35172-3 ; e-ISBN: 978-3-031-35173-0. — S. 254–265. — Bibliogr., Abstr.. — Publikacja dostępna online od: 2023-06-14. — F. Ciepiela, M. K. Nowak, D. Dworak - dod. afiliacja: APTIV Services Poland S. A., Jelesnia

2

BlurNet: keeping collected data private with a neural network based pipeline
BlurNet: keeping collected data private with a neural network based pipeline / Daniel DWORAK // W: Advanced, contemporary control : proceedings of KKA 2020 – the 20th Polish control conference : [14-16 October, 2020], Łódź, Poland / eds. Andrzej Bartoszewicz, Jacek Kabziński, Janusz Kacprzyk. — Cham : Springer Nature Switzerland AG, cop. 2020. — (Advances in Intelligent Systems and Computing ; ISSN 2194-5357 ; vol. 1196). — ISBN: 978-3-030-50935-4 ; e-ISBN: 978-3-030-50936-1. — S. 1237–1248. — Bibliogr. s. 1247-1248, Abstr.. — Dod. afiliacja autora: APTIV Services Poland S. A., Kraków, Poland

3

Cross-domain spatial matching for monocular 3D object detection
Cross-domain spatial matching for monocular 3D object detection / Daniel DWORAK, Jerzy BARANOWSKI // W: IECON 2023 [Dokument elektroniczny] : 49th annual conference of the IEEE Industrial Electronics Society : 16–19 October 2023 : Singapore. — Wersja do Windows. — Dane tekstowe. — [Piscataway] : IEEE, [2023]. — (Proceedings of the Annual Conference of the IEEE Industrial Electronics Society). — Dod. ISBN: 979-8-3503-3183-7. — e-ISBN: 979-8-3503-3182-0. — S. [1–6]. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. [6], Abstr.. — Publikacja dostępna online od: 2023-11-16. — D. Dworak - dod. afiliacja: Aptiv Services Poland SA, Krakow. — tekst: https://ieeexplore-1ieee-1org-1000047u9001f.wbg2.bg.agh.edu.pl/stamp/stamp.jsp?tp=&arnumber=10311851

4

Performance of LiDAR object detection deep learning architectures based on artificially generated point cloud data from CARLA simulator
Performance of LiDAR object detection deep learning architectures based on artificially generated point cloud data from CARLA simulator / Daniel DWORAK, Filip Ciepiela, Jakub Derbisz, Izzat Izzat, Mateusz Komorkiewicz, Mateusz Wójcik // W: MMAR 2019 : 24\textsuperscript{th} international conference on Methods and Models in Automation and Robotics : 26–29 August 2019, Międzyzdroje, Polska : abstracts. — Szczecin : ZAPOL Sobczyk, [2019]. — Dod. e-ISBN 978-1-7281-0933-6. — ISBN: 978-83-7518-922-3 ; e-ISBN: 978-1-7281-0932-9. — S. 72. — Pełny tekst w: MMAR 2019 [Dokument elektroniczny] : 24\textsuperscript{th} international conference on Methods and Models in Automation & Robotics : August 26–29, 2019, Międzyzdroje, Poland / Faculty of Electrical Engineering. West Pomeranian University of Technology Szczecin. — [Piscataway] : IEEE, cop. 2019. — Dysk Flash. — S. 600–605. — Wymagania systemowe: Adobe Reader. — Bibliogr. s. 605, Abstr. — Toż pod adresem {https://ieeexplore-1ieee-1org-1000047po00a9.wbg2.bg.agh.edu.pl/stamp/stamp.jsp?tp==8864642}