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  3. PollenFace - Face recognition for bioaerosol particle identification PollenFace - Face recognition for bioaerosol particle identification

PollenFace - Face recognition for bioaerosol particle identification

Identification of bioaerosol particles such as pollen and spores from digital holographic images with the same approach used for face recognition.

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

01.03.2022 - 31.08.2022

Overview

We seek a new process for aerosol particle identification which can easily deal with pollen and spores variations by country or plant life. Our idea is to switch from traditional image classification to the technology that is used for face recognition. This technology enables social media platforms and photo management software such as Facebook and Google Photos to recognise faces starting from a single face tag. Since we use holographic images as a main component for identification, we see very good opportunities for this approach.

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Facts

Type of project

Forschung

Internal organisations involved
  • Algorithmic Business F&E
Funding
  • Innosuisse - HSLU als Hauptforschungspartnerin (Main Research Partner)
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Persons involved: internal

Project manager
  • Simone Lionetti
Member of project team
  • Pascal Baumann
  • Fabian Gröger

Publications

  • Article, review; not peer reviewed (1)

    • Willi, Adrian; Baumann, Pascal; Erb, Sophie; Gröger, Fabian; Lionetti, Simone & Zeder, Yanick (14.06.2024). Self-Supervised and Few-Shot Learning for Robust Bioaerosol Monitoring. arXiv preprint,

Brief information

School:

Computer Science and Information Technology

Status:

Completed

Period:

03/01/2022 - 08/31/2022

Project Head

Simone Lionetti

Co-Head a.i. Applied AI Research Lab

+41 41 757 68 76

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