Deep learning for particulate matter sensing
Deep learning for particulate matter sensing
Airborne pollution is linked to illnesses such as cancer, heart disease and dementia. Recent breakthroughs in deep learning have now enabled the identification of single airborne particles in real-time, directly from their scattering patterns.
Mills, Benjamin
05f1886e-96ef-420f-b856-4115f4ab36d0
Grant-Jacob, James
c5d144d8-3c43-4195-8e80-edd96bfda91b
Mills, Benjamin
05f1886e-96ef-420f-b856-4115f4ab36d0
Grant-Jacob, James
c5d144d8-3c43-4195-8e80-edd96bfda91b
Mills, Benjamin and Grant-Jacob, James
(2022)
Deep learning for particulate matter sensing.
In Optics and Photonics for Sensing the Environment.
Optica Publishing Group..
(In Press)
Record type:
Conference or Workshop Item
(Paper)
Abstract
Airborne pollution is linked to illnesses such as cancer, heart disease and dementia. Recent breakthroughs in deep learning have now enabled the identification of single airborne particles in real-time, directly from their scattering patterns.
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Accepted/In Press date: 22 March 2022
Venue - Dates:
Optics and Photonics for Sensing the Environment, , Vancouver, Canada, 2022-07-11 - 2022-07-15
Identifiers
Local EPrints ID: 456289
URI: http://eprints.soton.ac.uk/id/eprint/456289
PURE UUID: 291a403a-8061-4d3d-84f3-a5422acb1e5f
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Date deposited: 27 Apr 2022 01:26
Last modified: 23 Feb 2023 02:56
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