---
_id: '66245'
abstract:
- lang: eng
  text: <jats:p>A mobile system that can detect viruses in real time is urgently needed,
    due to the combination of virus emergence and evolution with increasing global
    travel and transport. A biosensor called PAMONO (for Plasmon Assisted Microscopy
    of Nano-sized Objects) represents a viable technology for mobile real-time detection
    of viruses and virus-like particles. It could be used for fast and reliable diagnoses
    in hospitals, airports, the open air, or other settings. For analysis of the images
    provided by the sensor, state-of-the-art methods based on convolutional neural
    networks (CNNs) can achieve high accuracy. However, such computationally intensive
    methods may not be suitable on most mobile systems. In this work, we propose nanoparticle
    classification approaches based on frequency domain analysis, which are less resource-intensive.
    We observe that on average the classification takes 29    μ   s per image for
    the Fourier features and 17    μ   s for the Haar wavelet features. Although the
    CNN-based method scores 1–2.5 percentage points higher in classification accuracy,
    it takes 3370    μ   s per image on the same platform. With these results, we
    identify and explore the trade-off between resource efficiency and classification
    performance for nanoparticle classification of images provided by the PAMONO sensor.</jats:p>
article_number: '4138'
author:
- first_name: Mikail
  full_name: Yayla, Mikail
  last_name: Yayla
- first_name: Anas
  full_name: Toma, Anas
  last_name: Toma
- first_name: Kuan-Hsun
  full_name: Chen, Kuan-Hsun
  last_name: Chen
- first_name: Jan Eric
  full_name: Lenssen, Jan Eric
  last_name: Lenssen
- first_name: Victoria
  full_name: Shpacovitch, Victoria
  last_name: Shpacovitch
- first_name: Roland
  full_name: Hergenröder, Roland
  last_name: Hergenröder
- first_name: Frank
  full_name: Weichert, Frank
  last_name: Weichert
- first_name: Jian-Jia
  full_name: Chen, Jian-Jia
  last_name: Chen
citation:
  ama: Yayla M, Toma A, Chen K-H, et al. Nanoparticle Classification Using Frequency
    Domain Analysis on Resource-Limited Platforms. <i>Sensors</i>. 2019;19(19). doi:<a
    href="https://doi.org/10.3390/s19194138">10.3390/s19194138</a>
  apa: Yayla, M., Toma, A., Chen, K.-H., Lenssen, J. E., Shpacovitch, V., Hergenröder,
    R., Weichert, F., &#38; Chen, J.-J. (2019). Nanoparticle Classification Using
    Frequency Domain Analysis on Resource-Limited Platforms. <i>Sensors</i>, <i>19</i>(19),
    Article 4138. <a href="https://doi.org/10.3390/s19194138">https://doi.org/10.3390/s19194138</a>
  bibtex: '@article{Yayla_Toma_Chen_Lenssen_Shpacovitch_Hergenröder_Weichert_Chen_2019,
    title={Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited
    Platforms}, volume={19}, DOI={<a href="https://doi.org/10.3390/s19194138">10.3390/s19194138</a>},
    number={194138}, journal={Sensors}, publisher={MDPI AG}, author={Yayla, Mikail
    and Toma, Anas and Chen, Kuan-Hsun and Lenssen, Jan Eric and Shpacovitch, Victoria
    and Hergenröder, Roland and Weichert, Frank and Chen, Jian-Jia}, year={2019} }'
  chicago: Yayla, Mikail, Anas Toma, Kuan-Hsun Chen, Jan Eric Lenssen, Victoria Shpacovitch,
    Roland Hergenröder, Frank Weichert, and Jian-Jia Chen. “Nanoparticle Classification
    Using Frequency Domain Analysis on Resource-Limited Platforms.” <i>Sensors</i>
    19, no. 19 (2019). <a href="https://doi.org/10.3390/s19194138">https://doi.org/10.3390/s19194138</a>.
  ieee: 'M. Yayla <i>et al.</i>, “Nanoparticle Classification Using Frequency Domain
    Analysis on Resource-Limited Platforms,” <i>Sensors</i>, vol. 19, no. 19, Art.
    no. 4138, 2019, doi: <a href="https://doi.org/10.3390/s19194138">10.3390/s19194138</a>.'
  mla: Yayla, Mikail, et al. “Nanoparticle Classification Using Frequency Domain Analysis
    on Resource-Limited Platforms.” <i>Sensors</i>, vol. 19, no. 19, 4138, MDPI AG,
    2019, doi:<a href="https://doi.org/10.3390/s19194138">10.3390/s19194138</a>.
  short: M. Yayla, A. Toma, K.-H. Chen, J.E. Lenssen, V. Shpacovitch, R. Hergenröder,
    F. Weichert, J.-J. Chen, Sensors 19 (2019).
date_created: 2026-07-05T14:35:15Z
date_updated: 2026-07-05T14:43:54Z
doi: 10.3390/s19194138
intvolume: '        19'
issue: '19'
language:
- iso: eng
publication: Sensors
publication_identifier:
  issn:
  - 1424-8220
publication_status: published
publisher: MDPI AG
status: public
title: Nanoparticle Classification Using Frequency Domain Analysis on Resource-Limited
  Platforms
type: journal_article
user_id: '128464'
volume: 19
year: '2019'
...