Pascal Sager

Tätigkeit an der ZHAW als

Wissenschaftlicher Assistent AI/ML

https://www.zhaw.ch/en/engineering/institutes-centres/cai/computer-vision-perception-and-cognition-group/

Arbeits- und Forschungsschwerpunkte, Spezialkenntnisse

Deep Learning, Computer Vision, Object Recognition

Aus- und Fortbildung

- Bachelor in Computer Science, Zurich University of Applied Sciences, 2020

Beruflicher Werdegang

2018-2020: Software Engineer, Spühl GmbH
2015-2017: Software Engineer PLC, L. Kellenberger & Co. AG
2013-2015: Hardware Design Engineer, Spühl GmbH

Mitglied in Netzwerken

• Datalab, the ZHAW Data Science Laboratory
• CLAIRE, the Confederation of Laboratories for Artificial Intelligence Research in Europe
• data innovation alliance
• LinkedIn

• AUTODIDACT – Automated Video Data Annotation to Empower the ICU Cockpit Platform for Clinical Decision Support / Teammitglied / Projekt laufend
• RealScore – Scanning of Real-World Sheet Music for a Digital Music Stand / Teammitglied / Projekt laufend
• FWA: Visual Food Waste Analysis for Sustainable Kitchens / Teammitglied / Projekt abgeschlossen

• Simmler, Niclas; Sager, Pascal; Andermatt, Philipp; Chavarriaga, Ricardo; Schilling, Frank-Peter; Rosenthal, Matthias; Stadelmann, Thilo,

  2021.

  A survey of un-, weakly-, and semi-supervised learning methods for noisy, missing and partial labels in industrial vision applications [Paper].

  In:

  Proceedings of the 8th SDS.

  8th Swiss Conference on Data Science, Lucerne, Switzerland, 9 June 2021.

  IEEE.

  S. 26-31.

  Verfügbar unter: https://doi.org/10.1109/SDS51136.2021.00012

Zurück