Harnessing mmWave signals and machine learning for noninvasive taxonomic classification of insects.

Antony L, White C, Marchetti N, Donohue I, Stout JC, Narbudowicz A

DOI: 10.1093/pnasnexus/pgag096
Published: 2026 Apr
Container: PNAS nexus
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1093/pnasnexus/pgag096,
  title = {Harnessing mmWave signals and machine learning for noninvasive taxonomic classification of insects.},
  author = {Antony L and White C and Marchetti N and Donohue I and Stout JC and Narbudowicz A},
  year = {2026},
  journal = {PNAS nexus},
  doi = {10.1093/pnasnexus/pgag096},
  url = {https://doi.org/10.1093/pnasnexus/pgag096}
}

RIS

TY  - JOUR
TI  - Harnessing mmWave signals and machine learning for noninvasive taxonomic classification of insects.
AU  - Antony L
AU  - White C
AU  - Marchetti N
AU  - Donohue I
AU  - Stout JC
AU  - Narbudowicz A
PY  - 2026
JO  - PNAS nexus
DO  - 10.1093/pnasnexus/pgag096
UR  - https://doi.org/10.1093/pnasnexus/pgag096
ER  -

APA

L, A., C, W., N, M., I, D., JC, S., & A, N. (2026). Harnessing mmWave signals and machine learning for noninvasive taxonomic classification of insects.. PNAS nexus. https://doi.org/10.1093/pnasnexus/pgag096

Source records

pubmed · retrieved 2026-11-10T11:51:22.669Z