Please use this identifier to cite or link to this item: http://hdl.handle.net/10125/50247

Image Recognition of Disease-Carrying Insects: A System for Combating Infectious Diseases Using Image Classification Techniques and Citizen Science

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dc.contributor.author Munoz, J. Pablo
dc.contributor.author Boger, Rebecca
dc.contributor.author Dexter, Scott
dc.contributor.author Low, Russanne
dc.contributor.author Li, Justin
dc.date.accessioned 2017-12-28T01:44:11Z
dc.date.available 2017-12-28T01:44:11Z
dc.date.issued 2018-01-03
dc.identifier.isbn 978-0-9981331-1-9
dc.identifier.uri http://hdl.handle.net/10125/50247
dc.description.abstract We propose a system that assists infectious disease experts in the rapid identification of potential outbreaks resulting from arboviruses (mosquito, ticks, and other arthropod-borne viruses). The proposed system currently identifies mosquito larvae in images received from citizen scientists. Mosquito-borne viruses, such as the recent outbreak of Zika virus, can have devastating consequences in affected communities. We describe the first implemented prototype of our system, which includes modules for image collection, training of image classifiers, specimen recognition, and expert validation and analytics. The results of the recognition of specimens in images provided by citizen scientists can be used to generate visualizations of geographical regions of interest where the threat of an arbovirus may be imminent. Our system uses state-of-the-art image classification algorithms and a combination of mobile and desktop applications to ensure that crucial information is shared appropriately and accordingly among its users.
dc.format.extent 10 pages
dc.language.iso eng
dc.relation.ispartof Proceedings of the 51st Hawaii International Conference on System Sciences
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International
dc.rights.uri https://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Global Health IT Strategies
dc.subject Citizen Science, Image Classification, Machine Learning, Mobile Systems, Virus Outbreak
dc.title Image Recognition of Disease-Carrying Insects: A System for Combating Infectious Diseases Using Image Classification Techniques and Citizen Science
dc.type Conference Paper
dc.type.dcmi Text
dc.identifier.doi 10.24251/HICSS.2018.359
Appears in Collections: Global Health IT Strategies


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